Dataset Preview
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: Couldn't cast array of type list<item: int64> to int64
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
self._write_table(pa_table, writer_batch_size=writer_batch_size)
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2303, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1852, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2143, in cast_array_to_feature
return array_cast(
array,
...<2 lines>...
allow_decimal_to_str=allow_decimal_to_str,
)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1854, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2007, in array_cast
raise TypeError(f"Couldn't cast array of type {_short_str(array.type)} to {_short_str(pa_type)}")
TypeError: Couldn't cast array of type list<item: int64> to int64
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1869, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
model list | dataset string | modality string | row_no int64 | features dict | target dict | predicted dict | example string | q_type int64 | q string |
|---|---|---|---|---|---|---|---|---|---|
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 21,414 | {
"age": 57,
"workclass": "Local-gov",
"fnlwgt": 44273,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Widowed",
"occupation": "Transport-moving",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"n... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 18,785 | {
"age": 61,
"workclass": "Private",
"fnlwgt": 146788,
"education": "7th-8th",
"education-num": 4,
"marital-status": "Married-civ-spouse",
"occupation": "Transport-moving",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 29,811 | {
"age": 39,
"workclass": "Private",
"fnlwgt": 174330,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Separated",
"occupation": "Craft-repair",
"relationship": "Unmarried",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"native-cou... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 34,486 | {
"age": 35,
"workclass": "Private",
"fnlwgt": 27408,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Sales",
"relationship": "Not-in-family",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nati... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 32,162 | {
"age": 30,
"workclass": "Private",
"fnlwgt": 302473,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Adm-clerical",
"relationship": "Own-child",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nati... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 15,313 | {
"age": 27,
"workclass": "Private",
"fnlwgt": 160291,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Adm-clerical",
"relationship": "Unmarried",
"race": "Black",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 15,176 | {
"age": 36,
"workclass": "Private",
"fnlwgt": 150057,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 50,
... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 45,653 | {
"age": 42,
"workclass": "Private",
"fnlwgt": 22831,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Other-service",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 9,800 | {
"age": 17,
"workclass": "Private",
"fnlwgt": 147069,
"education": "11th",
"education-num": 7,
"marital-status": "Never-married",
"occupation": "Other-service",
"relationship": "Own-child",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 16,
"native... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 28,387 | {
"age": 33,
"workclass": "State-gov",
"fnlwgt": 174171,
"education": "Some-college",
"education-num": 10,
"marital-status": "Separated",
"occupation": "Tech-support",
"relationship": "Not-in-family",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 12,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 37,795 | {
"age": 40,
"workclass": "Private",
"fnlwgt": 124692,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Married-civ-spouse",
"occupation": "Exec-managerial",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 38,572 | {
"age": 35,
"workclass": "Private",
"fnlwgt": 188972,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Widowed",
"occupation": "Exec-managerial",
"relationship": "Unmarried",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 30,
"native-... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 38,457 | {
"age": 22,
"workclass": "Private",
"fnlwgt": 137591,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Sales",
"relationship": "Own-child",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 35,
"native-... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 24,057 | {
"age": 27,
"workclass": "Private",
"fnlwgt": 109997,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Divorced",
"occupation": "Other-service",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nati... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 8,688 | {
"age": 68,
"workclass": "Self-emp-not-inc",
"fnlwgt": 150904,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Widowed",
"occupation": "Craft-repair",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 35,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 33,515 | {
"age": 57,
"workclass": "Private",
"fnlwgt": 266189,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Divorced",
"occupation": "Adm-clerical",
"relationship": "Unmarried",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 42,
"native-co... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 47,243 | {
"age": 35,
"workclass": "Private",
"fnlwgt": 301862,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Craft-repair",
"relationship": "Unmarried",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 50,
"native... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 45,037 | {
"age": 25,
"workclass": "Private",
"fnlwgt": 167031,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Other-service",
"relationship": "Other-relative",
"race": "Other",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week":... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 29,415 | {
"age": 41,
"workclass": "State-gov",
"fnlwgt": 180272,
"education": "Masters",
"education-num": 14,
"marital-status": "Never-married",
"occupation": "Prof-specialty",
"relationship": "Own-child",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 35,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 32,048 | {
"age": 35,
"workclass": "Private",
"fnlwgt": 81232,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Married-civ-spouse",
"occupation": "Sales",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 15024,
"capital-loss": 0,
"hours-per-week": 50,
"nati... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 30,669 | {
"age": 21,
"workclass": "Private",
"fnlwgt": 179720,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Other-service",
"relationship": "Other-relative",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 30,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 26,148 | {
"age": 37,
"workclass": "Private",
"fnlwgt": 227545,
"education": "Some-college",
"education-num": 10,
"marital-status": "Married-civ-spouse",
"occupation": "Sales",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 44,
"nati... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 47,537 | {
"age": 52,
"workclass": "Self-emp-not-inc",
"fnlwgt": 34973,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Married-civ-spouse",
"occupation": "Farming-fishing",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 1887,
"hours-per-wee... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 40,160 | {
"age": 38,
"workclass": "State-gov",
"fnlwgt": 188303,
"education": "Some-college",
"education-num": 10,
"marital-status": "Married-civ-spouse",
"occupation": "Protective-serv",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 7688,
"capital-loss": 0,
"hours-per-wee... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 6,403 | {
"age": 46,
"workclass": "Private",
"fnlwgt": 411595,
"education": "5th-6th",
"education-num": 3,
"marital-status": "Widowed",
"occupation": "Machine-op-inspct",
"relationship": "Unmarried",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nativ... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 27,209 | {
"age": 23,
"workclass": "Private",
"fnlwgt": 113466,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Craft-repair",
"relationship": "Not-in-family",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"na... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 10,348 | {
"age": 58,
"workclass": "Private",
"fnlwgt": 141379,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Divorced",
"occupation": "Adm-clerical",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 42,
"nativ... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 3,280 | {
"age": 18,
"workclass": "Private",
"fnlwgt": 122988,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Handlers-cleaners",
"relationship": "Own-child",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 20,
"n... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 39,579 | {
"age": 21,
"workclass": "Private",
"fnlwgt": 83704,
"education": "12th",
"education-num": 8,
"marital-status": "Married-civ-spouse",
"occupation": "Craft-repair",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"native-... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 23,484 | {
"age": 40,
"workclass": "Self-emp-not-inc",
"fnlwgt": 238574,
"education": "Prof-school",
"education-num": 15,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-w... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 25,727 | {
"age": 28,
"workclass": "Private",
"fnlwgt": 398220,
"education": "5th-6th",
"education-num": 3,
"marital-status": "Never-married",
"occupation": "Craft-repair",
"relationship": "Other-relative",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"n... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 39,598 | {
"age": 33,
"workclass": "Private",
"fnlwgt": 246038,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 6,742 | {
"age": 41,
"workclass": "Private",
"fnlwgt": 160893,
"education": "Assoc-acdm",
"education-num": 12,
"marital-status": "Never-married",
"occupation": "Adm-clerical",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 45,... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 32,508 | {
"age": 54,
"workclass": "Private",
"fnlwgt": 210736,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Married-civ-spouse",
"occupation": "Craft-repair",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nat... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 6,255 | {
"age": 40,
"workclass": "Self-emp-not-inc",
"fnlwgt": 145441,
"education": "Some-college",
"education-num": 10,
"marital-status": "Divorced",
"occupation": "Exec-managerial",
"relationship": "Unmarried",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": ... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 47,661 | {
"age": 47,
"workclass": "Private",
"fnlwgt": 252079,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Married-civ-spouse",
"occupation": "Machine-op-inspct",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 7688,
"capital-loss": 0,
"hours-per-week":... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 13,808 | {
"age": 49,
"workclass": "Private",
"fnlwgt": 118520,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Divorced",
"occupation": "Adm-clerical",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 45,
"nativ... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 22,639 | {
"age": 45,
"workclass": "Local-gov",
"fnlwgt": 148222,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Adm-clerical",
"relationship": "Not-in-family",
"race": "Black",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 42,663 | {
"age": 47,
"workclass": "Private",
"fnlwgt": 431515,
"education": "Assoc-voc",
"education-num": 11,
"marital-status": "Married-civ-spouse",
"occupation": "Craft-repair",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 18,148 | {
"age": 36,
"workclass": "Federal-gov",
"fnlwgt": 128884,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Divorced",
"occupation": "Adm-clerical",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 48,
"n... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 21,762 | {
"age": 19,
"workclass": "Self-emp-not-inc",
"fnlwgt": 30800,
"education": "10th",
"education-num": 6,
"marital-status": "Married-spouse-absent",
"occupation": "Adm-clerical",
"relationship": "Unmarried",
"race": "Amer-Indian-Eskimo",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"ho... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 20,071 | {
"age": 47,
"workclass": "Private",
"fnlwgt": 140664,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Divorced",
"occupation": "Sales",
"relationship": "Not-in-family",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 45,
"native-coun... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 39,213 | {
"age": 23,
"workclass": "Private",
"fnlwgt": 520759,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Other-service",
"relationship": "Not-in-family",
"race": "Black",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 30,
"n... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 28,662 | {
"age": 44,
"workclass": "State-gov",
"fnlwgt": 691903,
"education": "Masters",
"education-num": 14,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "Black",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 60,
... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 7,234 | {
"age": 40,
"workclass": "Self-emp-inc",
"fnlwgt": 115411,
"education": "Assoc-acdm",
"education-num": 12,
"marital-status": "Married-civ-spouse",
"occupation": "Exec-managerial",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week"... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 42,284 | {
"age": 33,
"workclass": "Private",
"fnlwgt": 341187,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Married-civ-spouse",
"occupation": "Exec-managerial",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 50,
... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 46,692 | {
"age": 29,
"workclass": "Private",
"fnlwgt": 327779,
"education": "Some-college",
"education-num": 10,
"marital-status": "Married-civ-spouse",
"occupation": "Handlers-cleaners",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week":... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 48,236 | {
"age": 46,
"workclass": "Local-gov",
"fnlwgt": 267952,
"education": "Assoc-voc",
"education-num": 11,
"marital-status": "Divorced",
"occupation": "Exec-managerial",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 36,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 42,099 | {
"age": 45,
"workclass": "Local-gov",
"fnlwgt": 235431,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Separated",
"occupation": "Other-service",
"relationship": "Unmarried",
"race": "Black",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nativ... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 20,145 | {
"age": 50,
"workclass": "State-gov",
"fnlwgt": 229272,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Married-civ-spouse",
"occupation": "Craft-repair",
"relationship": "Husband",
"race": "Black",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"n... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 23,205 | {
"age": 38,
"workclass": "Private",
"fnlwgt": 119177,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Married-civ-spouse",
"occupation": "Sales",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"native-... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 45,406 | {
"age": 24,
"workclass": "Private",
"fnlwgt": 143766,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Machine-op-inspct",
"relationship": "Own-child",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 55... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 38,810 | {
"age": 22,
"workclass": "Private",
"fnlwgt": 185452,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Never-married",
"occupation": "Exec-managerial",
"relationship": "Own-child",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 34,749 | {
"age": 34,
"workclass": "Private",
"fnlwgt": 209691,
"education": "Assoc-voc",
"education-num": 11,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 4386,
"capital-loss": 0,
"hours-per-week": 50... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 24,519 | {
"age": 62,
"workclass": "Private",
"fnlwgt": 113080,
"education": "7th-8th",
"education-num": 4,
"marital-status": "Divorced",
"occupation": "Craft-repair",
"relationship": "Own-child",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"native-coun... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 17,704 | {
"age": 41,
"workclass": "Private",
"fnlwgt": 184102,
"education": "11th",
"education-num": 7,
"marital-status": "Divorced",
"occupation": "Other-service",
"relationship": "Not-in-family",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"native-co... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 11,716 | {
"age": 25,
"workclass": "Private",
"fnlwgt": 161631,
"education": "Some-college",
"education-num": 10,
"marital-status": "Married-civ-spouse",
"occupation": "Craft-repair",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 42,725 | {
"age": 43,
"workclass": "Private",
"fnlwgt": 76460,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Adm-clerical",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"n... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 609 | {
"age": 33,
"workclass": "Local-gov",
"fnlwgt": 217304,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Never-married",
"occupation": "Adm-clerical",
"relationship": "Not-in-family",
"race": "Black",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 11,823 | {
"age": 35,
"workclass": "Private",
"fnlwgt": 282753,
"education": "Assoc-voc",
"education-num": 11,
"marital-status": "Married-civ-spouse",
"occupation": "Craft-repair",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 44,599 | {
"age": 38,
"workclass": "Self-emp-not-inc",
"fnlwgt": 194534,
"education": "Masters",
"education-num": 14,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "Black",
"sex": "Male",
"capital-gain": 99999,
"capital-loss": 0,
"hours-per-w... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 39,633 | {
"age": 28,
"workclass": "Private",
"fnlwgt": 207513,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Sales",
"relationship": "Own-child",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 48,
"native-countr... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 17,088 | {
"age": 33,
"workclass": "Private",
"fnlwgt": 169879,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 3103,
"capital-loss": 0,
"hours-per-week": 47... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 20,270 | {
"age": 22,
"workclass": "Private",
"fnlwgt": 191324,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Protective-serv",
"relationship": "Own-child",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 25,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 42,112 | {
"age": 31,
"workclass": "Private",
"fnlwgt": 147284,
"education": "Doctorate",
"education-num": 16,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 1977,
"hours-per-week": 99... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 4,484 | {
"age": 18,
"workclass": "Private",
"fnlwgt": 217942,
"education": "11th",
"education-num": 7,
"marital-status": "Never-married",
"occupation": "Other-service",
"relationship": "Own-child",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 24,
"native-c... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 34,474 | {
"age": 52,
"workclass": "Private",
"fnlwgt": 110748,
"education": "Masters",
"education-num": 14,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 50,
"... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 20,488 | {
"age": 64,
"workclass": "Private",
"fnlwgt": 321166,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Divorced",
"occupation": "Sales",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 5,
"native-cou... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 40,272 | {
"age": 62,
"workclass": "Private",
"fnlwgt": 345780,
"education": "Assoc-voc",
"education-num": 11,
"marital-status": "Divorced",
"occupation": "Other-service",
"relationship": "Not-in-family",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nat... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 37,771 | {
"age": 19,
"workclass": "Private",
"fnlwgt": 146679,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Exec-managerial",
"relationship": "Own-child",
"race": "Black",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 30,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 44,934 | {
"age": 22,
"workclass": "Private",
"fnlwgt": 315974,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Sales",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"n... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 15,970 | {
"age": 38,
"workclass": "Federal-gov",
"fnlwgt": 455379,
"education": "12th",
"education-num": 8,
"marital-status": "Married-civ-spouse",
"occupation": "Protective-serv",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 56,
... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 28,750 | {
"age": 27,
"workclass": "Private",
"fnlwgt": 256764,
"education": "Assoc-acdm",
"education-num": 12,
"marital-status": "Never-married",
"occupation": "Sales",
"relationship": "Not-in-family",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nativ... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 33,876 | {
"age": 33,
"workclass": "Private",
"fnlwgt": 301867,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Adm-clerical",
"relationship": "Unmarried",
"race": "Asian-Pac-Islander",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 12,740 | {
"age": 22,
"workclass": "Private",
"fnlwgt": 193190,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Other-service",
"relationship": "Own-child",
"race": "Black",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nat... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 3,797 | {
"age": 39,
"workclass": "Private",
"fnlwgt": 346478,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Married-civ-spouse",
"occupation": "Sales",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"native-cou... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 7,814 | {
"age": 36,
"workclass": "Private",
"fnlwgt": 120204,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Divorced",
"occupation": "Tech-support",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nativ... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 12,311 | {
"age": 24,
"workclass": "Private",
"fnlwgt": 88824,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Never-married",
"occupation": "Tech-support",
"relationship": "Not-in-family",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 12,899 | {
"age": 44,
"workclass": "Local-gov",
"fnlwgt": 185267,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 1902,
"hours-per-week": ... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 22,634 | {
"age": 29,
"workclass": "Private",
"fnlwgt": 301031,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Married-civ-spouse",
"occupation": "Transport-moving",
"relationship": "Husband",
"race": "Black",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 14,472 | {
"age": 23,
"workclass": "Private",
"fnlwgt": 114939,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Sales",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 38,
"n... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 11,797 | {
"age": 32,
"workclass": "Private",
"fnlwgt": 264554,
"education": "Some-college",
"education-num": 10,
"marital-status": "Married-civ-spouse",
"occupation": "Tech-support",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 40,892 | {
"age": 46,
"workclass": "Private",
"fnlwgt": 191204,
"education": "Assoc-voc",
"education-num": 11,
"marital-status": "Never-married",
"occupation": "Exec-managerial",
"relationship": "Own-child",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 26,763 | {
"age": 42,
"workclass": "Self-emp-inc",
"fnlwgt": 130126,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Married-civ-spouse",
"occupation": "Prof-specialty",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 1977,
"hours-per-week... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 6,353 | {
"age": 37,
"workclass": "Private",
"fnlwgt": 318168,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Machine-op-inspct",
"relationship": "Not-in-family",
"race": "Black",
"sex": "Male",
"capital-gain": 1055,
"capital-loss": 0,
"hours-per-week": 2... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 39,467 | {
"age": 24,
"workclass": "Private",
"fnlwgt": 62952,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Craft-repair",
"relationship": "Own-child",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"native-... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 25,490 | {
"age": 22,
"workclass": "Private",
"fnlwgt": 318915,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Other-service",
"relationship": "Unmarried",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nat... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 8,276 | {
"age": 48,
"workclass": "Private",
"fnlwgt": 166863,
"education": "Masters",
"education-num": 14,
"marital-status": "Married-civ-spouse",
"occupation": "Exec-managerial",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 9,743 | {
"age": 38,
"workclass": "Private",
"fnlwgt": 35890,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Married-civ-spouse",
"occupation": "Transport-moving",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 24,699 | {
"age": 31,
"workclass": "Private",
"fnlwgt": 369825,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Never-married",
"occupation": "Sales",
"relationship": "Not-in-family",
"race": "White",
"sex": "Male",
"capital-gain": 4101,
"capital-loss": 0,
"hours-per-week": 50,
"nat... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 24,799 | {
"age": 29,
"workclass": "Private",
"fnlwgt": 229729,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Transport-moving",
"relationship": "Not-in-family",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 36,908 | {
"age": 34,
"workclass": "Private",
"fnlwgt": 125279,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Married-civ-spouse",
"occupation": "Transport-moving",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 42,736 | {
"age": 29,
"workclass": "Private",
"fnlwgt": 202878,
"education": "7th-8th",
"education-num": 4,
"marital-status": "Married-civ-spouse",
"occupation": "Farming-fishing",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 2042,
"hours-per-week": 40,
... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 1,028 | {
"age": 27,
"workclass": "Private",
"fnlwgt": 216479,
"education": "Bachelors",
"education-num": 13,
"marital-status": "Never-married",
"occupation": "Sales",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nati... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 42,694 | {
"age": 23,
"workclass": "Private",
"fnlwgt": 45713,
"education": "Some-college",
"education-num": 10,
"marital-status": "Never-married",
"occupation": "Craft-repair",
"relationship": "Other-relative",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 6,882 | {
"age": 29,
"workclass": "Private",
"fnlwgt": 132675,
"education": "11th",
"education-num": 7,
"marital-status": "Separated",
"occupation": "Other-service",
"relationship": "Own-child",
"race": "Black",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"native-cou... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 4,618 | {
"age": 18,
"workclass": "Local-gov",
"fnlwgt": 28357,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Adm-clerical",
"relationship": "Own-child",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 40,
"nat... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 20,015 | {
"age": 18,
"workclass": "Private",
"fnlwgt": 148644,
"education": "HS-grad",
"education-num": 9,
"marital-status": "Never-married",
"occupation": "Sales",
"relationship": "Own-child",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 28,
"native-coun... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 9,857 | {
"age": 57,
"workclass": "Self-emp-not-inc",
"fnlwgt": 200316,
"education": "7th-8th",
"education-num": 4,
"marital-status": "Married-civ-spouse",
"occupation": "Craft-repair",
"relationship": "Husband",
"race": "White",
"sex": "Male",
"capital-gain": 0,
"capital-loss": 0,
"hours-per-week": 5... | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | {
"value": "<=50K",
"label": "less than or equal to 50K"
} | The model predicted the individual's income to be less than or equal to 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
[
"TwoLayerNN",
"TabNN"
] | Adult Census | tabular | 48,592 | {
"age": 54,
"workclass": "Private",
"fnlwgt": 161691,
"education": "Masters",
"education-num": 14,
"marital-status": "Divorced",
"occupation": "Prof-specialty",
"relationship": "Not-in-family",
"race": "White",
"sex": "Female",
"capital-gain": 0,
"capital-loss": 2559,
"hours-per-week": 40,
... | {
"value": ">50K",
"label": "greater than 50K"
} | {
"value": ">50K",
"label": "greater than 50K"
} | The model predicted the individual's income to be greater than 50K. Which input features were most responsible for this prediction? | 1 | Which part of the input was most responsible for the model’s prediction? |
End of preview.
No dataset card yet
- Downloads last month
- 116