harithapliyal/autotrain-tatanic-survival-51030121311
Tabular Classification
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_data_files
list | _fingerprint
string | _format_columns
sequence | _format_kwargs
dict | _format_type
null | _output_all_columns
bool | _split
null |
|---|---|---|---|---|---|---|
[
{
"filename": "data-00000-of-00001.arrow"
}
] | 347bd28012bdcd62 | [
"feat_Age",
"feat_Cabin",
"feat_Embarked",
"feat_Fare",
"feat_Name",
"feat_Parch",
"feat_Pclass",
"feat_Sex",
"feat_SibSp",
"feat_Ticket",
"id",
"target"
] | {} | null | false | null |
AutoTrain Dataset for project: tatanic-survival
Dataset Description
This dataset has been automatically processed by AutoTrain for project tatanic-survival.
Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"id": 297,
"target": 0,
"feat_Pclass": 3,
"feat_Name": "Hanna, Mr. Mansour",
"feat_Sex": "male",
"feat_Age": 23.5,
"feat_SibSp": 0,
"feat_Parch": 0,
"feat_Ticket": "2693",
"feat_Fare": 7.2292,
"feat_Cabin": null,
"feat_Embarked": "C"
},
{
"id": 4,
"target": 1,
"feat_Pclass": 1,
"feat_Name": "Futrelle, Mrs. Jacques Heath (Lily May Peel)",
"feat_Sex": "female",
"feat_Age": 35.0,
"feat_SibSp": 1,
"feat_Parch": 0,
"feat_Ticket": "113803",
"feat_Fare": 53.1,
"feat_Cabin": "C123",
"feat_Embarked": "S"
}
]
Dataset Fields
The dataset has the following fields (also called "features"):
{
"id": "Value(dtype='int64', id=None)",
"target": "ClassLabel(names=['0', '1'], id=None)",
"feat_Pclass": "Value(dtype='int64', id=None)",
"feat_Name": "Value(dtype='string', id=None)",
"feat_Sex": "Value(dtype='string', id=None)",
"feat_Age": "Value(dtype='float64', id=None)",
"feat_SibSp": "Value(dtype='int64', id=None)",
"feat_Parch": "Value(dtype='int64', id=None)",
"feat_Ticket": "Value(dtype='string', id=None)",
"feat_Fare": "Value(dtype='float64', id=None)",
"feat_Cabin": "Value(dtype='string', id=None)",
"feat_Embarked": "Value(dtype='string', id=None)"
}
Dataset Splits
This dataset is split into a train and validation split. The split sizes are as follow:
| Split name | Num samples |
|---|---|
| train | 712 |
| valid | 179 |
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