Upload . with huggingface_hub
Browse files- README.md +16 -16
- config.json +9 -9
- confusion_matrix.png +0 -0
- umit_class_okl25.pkl +2 -2
README.md
CHANGED
|
@@ -8,17 +8,17 @@ model_file: umit_class_okl25.pkl
|
|
| 8 |
widget:
|
| 9 |
structuredData:
|
| 10 |
CO2:
|
| 11 |
-
-
|
| 12 |
-
-
|
| 13 |
-
-
|
| 14 |
Hum:
|
| 15 |
-
-
|
| 16 |
-
-
|
| 17 |
-
-
|
| 18 |
Temp:
|
| 19 |
-
-
|
| 20 |
-
- 22.3
|
| 21 |
- 23.1
|
|
|
|
| 22 |
---
|
| 23 |
|
| 24 |
# Model description
|
|
@@ -41,14 +41,14 @@ The model is trained with below hyperparameters.
|
|
| 41 |
| Hyperparameter | Value |
|
| 42 |
|-------------------------------------|-----------------------------------------------------------------------|
|
| 43 |
| memory | |
|
| 44 |
-
| steps | [('transform', FunctionTransformer(func=<function nan_to_num at
|
| 45 |
| verbose | False |
|
| 46 |
-
| transform | FunctionTransformer(func=<function nan_to_num at
|
| 47 |
| classifier | XGBClassifier(base_score=None, booster=None, callbacks=None,<br /> colsample_bylevel=None, colsample_bynode=None,<br /> colsample_bytree=None, early_stopping_rounds=None,<br /> enable_categorical=False, eval_metric=None, feature_types=None,<br /> gamma=None, gpu_id=None, grow_policy=None, importance_type=None,<br /> interaction_constraints=None, learning_rate=None, max_bin=None,<br /> max_cat_threshold=None, max_cat_to_onehot=None,<br /> max_delta_step=None, max_depth=None, max_leaves=None,<br /> min_child_weight=None, missing=nan, monotone_constraints=None,<br /> n_estimators=100, n_jobs=None, num_parallel_tree=None,<br /> predictor=None, random_state=None, ...) |
|
| 48 |
| transform__accept_sparse | False |
|
| 49 |
| transform__check_inverse | True |
|
| 50 |
| transform__feature_names_out | |
|
| 51 |
-
| transform__func | <function nan_to_num at
|
| 52 |
| transform__inv_kw_args | |
|
| 53 |
| transform__inverse_func | |
|
| 54 |
| transform__kw_args | |
|
|
@@ -100,7 +100,7 @@ The model is trained with below hyperparameters.
|
|
| 100 |
|
| 101 |
The model plot is below.
|
| 102 |
|
| 103 |
-
<style>#sk-container-id-
|
| 104 |
|
| 105 |
## Evaluation Results
|
| 106 |
|
|
@@ -108,10 +108,10 @@ You can find the details about evaluation process and the evaluation results.
|
|
| 108 |
|
| 109 |
| Metric | Value |
|
| 110 |
|-----------|----------|
|
| 111 |
-
| accuracy | 0.
|
| 112 |
-
| precision | 0.
|
| 113 |
-
| recall | 0.
|
| 114 |
-
| f1-score | 0.
|
| 115 |
|
| 116 |
# How to Get Started with the Model
|
| 117 |
|
|
|
|
| 8 |
widget:
|
| 9 |
structuredData:
|
| 10 |
CO2:
|
| 11 |
+
- 708
|
| 12 |
+
- 490
|
| 13 |
+
- 481
|
| 14 |
Hum:
|
| 15 |
+
- 31.3
|
| 16 |
+
- 31.8
|
| 17 |
+
- 44.9
|
| 18 |
Temp:
|
| 19 |
+
- 23.6
|
|
|
|
| 20 |
- 23.1
|
| 21 |
+
- 21.4
|
| 22 |
---
|
| 23 |
|
| 24 |
# Model description
|
|
|
|
| 41 |
| Hyperparameter | Value |
|
| 42 |
|-------------------------------------|-----------------------------------------------------------------------|
|
| 43 |
| memory | |
|
| 44 |
+
| steps | [('transform', FunctionTransformer(func=<function nan_to_num at 0x00000208B48C4A60>)), ('classifier', XGBClassifier(base_score=None, booster=None, callbacks=None,<br /> colsample_bylevel=None, colsample_bynode=None,<br /> colsample_bytree=None, early_stopping_rounds=None,<br /> enable_categorical=False, eval_metric=None, feature_types=None,<br /> gamma=None, gpu_id=None, grow_policy=None, importance_type=None,<br /> interaction_constraints=None, learning_rate=None, max_bin=None,<br /> max_cat_threshold=None, max_cat_to_onehot=None,<br /> max_delta_step=None, max_depth=None, max_leaves=None,<br /> min_child_weight=None, missing=nan, monotone_constraints=None,<br /> n_estimators=100, n_jobs=None, num_parallel_tree=None,<br /> predictor=None, random_state=None, ...))] |
|
| 45 |
| verbose | False |
|
| 46 |
+
| transform | FunctionTransformer(func=<function nan_to_num at 0x00000208B48C4A60>) |
|
| 47 |
| classifier | XGBClassifier(base_score=None, booster=None, callbacks=None,<br /> colsample_bylevel=None, colsample_bynode=None,<br /> colsample_bytree=None, early_stopping_rounds=None,<br /> enable_categorical=False, eval_metric=None, feature_types=None,<br /> gamma=None, gpu_id=None, grow_policy=None, importance_type=None,<br /> interaction_constraints=None, learning_rate=None, max_bin=None,<br /> max_cat_threshold=None, max_cat_to_onehot=None,<br /> max_delta_step=None, max_depth=None, max_leaves=None,<br /> min_child_weight=None, missing=nan, monotone_constraints=None,<br /> n_estimators=100, n_jobs=None, num_parallel_tree=None,<br /> predictor=None, random_state=None, ...) |
|
| 48 |
| transform__accept_sparse | False |
|
| 49 |
| transform__check_inverse | True |
|
| 50 |
| transform__feature_names_out | |
|
| 51 |
+
| transform__func | <function nan_to_num at 0x00000208B48C4A60> |
|
| 52 |
| transform__inv_kw_args | |
|
| 53 |
| transform__inverse_func | |
|
| 54 |
| transform__kw_args | |
|
|
|
|
| 100 |
|
| 101 |
The model plot is below.
|
| 102 |
|
| 103 |
+
<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: "▸";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id="sk-container-id-1" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>Pipeline(steps=[('transform',FunctionTransformer(func=<function nan_to_num at 0x00000208B48C4A60>)),('classifier',XGBClassifier(base_score=None, booster=None, callbacks=None,colsample_bylevel=None, colsample_bynode=None,colsample_bytree=None,early_stopping_rounds=None,enable_categorical=False, eval_metric=None,feature_types=None, gamma=None, gpu_id=None,grow_policy=None, importance_type=None,interaction_constraints=None, learning_rate=None,max_bin=None, max_cat_threshold=None,max_cat_to_onehot=None, max_delta_step=None,max_depth=None, max_leaves=None,min_child_weight=None, missing=nan,monotone_constraints=None, n_estimators=100,n_jobs=None, num_parallel_tree=None,predictor=None, random_state=None, ...))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-1" type="checkbox" ><label for="sk-estimator-id-1" class="sk-toggleable__label sk-toggleable__label-arrow">Pipeline</label><div class="sk-toggleable__content"><pre>Pipeline(steps=[('transform',FunctionTransformer(func=<function nan_to_num at 0x00000208B48C4A60>)),('classifier',XGBClassifier(base_score=None, booster=None, callbacks=None,colsample_bylevel=None, colsample_bynode=None,colsample_bytree=None,early_stopping_rounds=None,enable_categorical=False, eval_metric=None,feature_types=None, gamma=None, gpu_id=None,grow_policy=None, importance_type=None,interaction_constraints=None, learning_rate=None,max_bin=None, max_cat_threshold=None,max_cat_to_onehot=None, max_delta_step=None,max_depth=None, max_leaves=None,min_child_weight=None, missing=nan,monotone_constraints=None, n_estimators=100,n_jobs=None, num_parallel_tree=None,predictor=None, random_state=None, ...))])</pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-2" type="checkbox" ><label for="sk-estimator-id-2" class="sk-toggleable__label sk-toggleable__label-arrow">FunctionTransformer</label><div class="sk-toggleable__content"><pre>FunctionTransformer(func=<function nan_to_num at 0x00000208B48C4A60>)</pre></div></div></div><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-3" type="checkbox" ><label for="sk-estimator-id-3" class="sk-toggleable__label sk-toggleable__label-arrow">XGBClassifier</label><div class="sk-toggleable__content"><pre>XGBClassifier(base_score=None, booster=None, callbacks=None,colsample_bylevel=None, colsample_bynode=None,colsample_bytree=None, early_stopping_rounds=None,enable_categorical=False, eval_metric=None, feature_types=None,gamma=None, gpu_id=None, grow_policy=None, importance_type=None,interaction_constraints=None, learning_rate=None, max_bin=None,max_cat_threshold=None, max_cat_to_onehot=None,max_delta_step=None, max_depth=None, max_leaves=None,min_child_weight=None, missing=nan, monotone_constraints=None,n_estimators=100, n_jobs=None, num_parallel_tree=None,predictor=None, random_state=None, ...)</pre></div></div></div></div></div></div></div>
|
| 104 |
|
| 105 |
## Evaluation Results
|
| 106 |
|
|
|
|
| 108 |
|
| 109 |
| Metric | Value |
|
| 110 |
|-----------|----------|
|
| 111 |
+
| accuracy | 0.976744 |
|
| 112 |
+
| precision | 0.972624 |
|
| 113 |
+
| recall | 0.963504 |
|
| 114 |
+
| f1-score | 0.967959 |
|
| 115 |
|
| 116 |
# How to Get Started with the Model
|
| 117 |
|
config.json
CHANGED
|
@@ -11,19 +11,19 @@
|
|
| 11 |
],
|
| 12 |
"example_input": {
|
| 13 |
"CO2": [
|
| 14 |
-
|
| 15 |
-
|
| 16 |
-
|
| 17 |
],
|
| 18 |
"Hum": [
|
| 19 |
-
|
| 20 |
-
|
| 21 |
-
|
| 22 |
],
|
| 23 |
"Temp": [
|
| 24 |
-
|
| 25 |
-
|
| 26 |
-
|
| 27 |
]
|
| 28 |
},
|
| 29 |
"model": {
|
|
|
|
| 11 |
],
|
| 12 |
"example_input": {
|
| 13 |
"CO2": [
|
| 14 |
+
708,
|
| 15 |
+
490,
|
| 16 |
+
481
|
| 17 |
],
|
| 18 |
"Hum": [
|
| 19 |
+
31.3,
|
| 20 |
+
31.8,
|
| 21 |
+
44.9
|
| 22 |
],
|
| 23 |
"Temp": [
|
| 24 |
+
23.6,
|
| 25 |
+
23.1,
|
| 26 |
+
21.4
|
| 27 |
]
|
| 28 |
},
|
| 29 |
"model": {
|
confusion_matrix.png
CHANGED
|
|
umit_class_okl25.pkl
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a49e6359f3f38253d06e018c9d2541c4b22b74e7d047d0a961fc1eb3220c3a17
|
| 3 |
+
size 209545
|