| | --- |
| | library_name: sklearn |
| | tags: |
| | - sklearn |
| | - skops |
| | - tabular-classification |
| | model_format: pickle |
| | model_file: stroke_model.pkl |
| | widget: |
| | - structuredData: |
| | Residence_type_Rural: |
| | - true |
| | - true |
| | - false |
| | Residence_type_Urban: |
| | - false |
| | - false |
| | - true |
| | age: |
| | - 0.15771484375 |
| | - 0.7802734375 |
| | - 0.31640625 |
| | avg_glucose_level: |
| | - 0.24563752192779986 |
| | - 0.3366263502908319 |
| | - 0.04413258240236362 |
| | avg_glucose_level/bmi: |
| | - 0.35152096177583636 |
| | - 0.18922222093200816 |
| | - 0.12391183202584002 |
| | bmi: |
| | - 0.10487444608567206 |
| | - 0.35007385524372225 |
| | - 0.1920236336779911 |
| | ever_married_No: |
| | - true |
| | - false |
| | - true |
| | ever_married_Yes: |
| | - false |
| | - true |
| | - false |
| | gender_Female: |
| | - false |
| | - true |
| | - false |
| | gender_Male: |
| | - true |
| | - false |
| | - true |
| | gender_Other: |
| | - false |
| | - false |
| | - false |
| | heart_disease_No: |
| | - true |
| | - true |
| | - true |
| | heart_disease_Yes: |
| | - false |
| | - false |
| | - false |
| | hypertension_No: |
| | - true |
| | - true |
| | - true |
| | hypertension_Yes: |
| | - false |
| | - false |
| | - false |
| | smoking_status_Unknown: |
| | - false |
| | - false |
| | - false |
| | smoking_status_formerly smoked: |
| | - false |
| | - false |
| | - false |
| | smoking_status_never smoked: |
| | - true |
| | - false |
| | - false |
| | smoking_status_smokes: |
| | - false |
| | - true |
| | - true |
| | work_type_Govt_job: |
| | - false |
| | - false |
| | - false |
| | work_type_Never_worked: |
| | - false |
| | - false |
| | - false |
| | work_type_Private: |
| | - false |
| | - false |
| | - true |
| | work_type_Self-employed: |
| | - false |
| | - true |
| | - false |
| | work_type_children: |
| | - true |
| | - false |
| | - false |
| | --- |
| | |
| | # Model description |
| |
|
| | The model is intended to be used to predict if a person is likely to get a stroke or not |
| |
|
| | ## Intended uses & limitations |
| |
|
| | [More Information Needed] |
| |
|
| | ## Training Procedure |
| |
|
| | [More Information Needed] |
| |
|
| | ### Hyperparameters |
| |
|
| | <details> |
| | <summary> Click to expand </summary> |
| |
|
| | | Hyperparameter | Value | |
| | |-------------------------|---------------------| |
| | | objective | binary:logistic | |
| | | base_score | | |
| | | booster | | |
| | | callbacks | | |
| | | colsample_bylevel | 0.9076228511174643 | |
| | | colsample_bynode | | |
| | | colsample_bytree | 0.8045246933821307 | |
| | | device | | |
| | | early_stopping_rounds | | |
| | | enable_categorical | False | |
| | | eval_metric | | |
| | | feature_types | | |
| | | gamma | | |
| | | grow_policy | | |
| | | importance_type | | |
| | | interaction_constraints | | |
| | | learning_rate | 0.0711965541329635 | |
| | | max_bin | | |
| | | max_cat_threshold | | |
| | | max_cat_to_onehot | | |
| | | max_delta_step | | |
| | | max_depth | | |
| | | max_leaves | 4 | |
| | | min_child_weight | 0.27994747825685384 | |
| | | missing | nan | |
| | | monotone_constraints | | |
| | | multi_strategy | | |
| | | n_estimators | 35 | |
| | | n_jobs | | |
| | | num_parallel_tree | | |
| | | random_state | | |
| | | reg_alpha | 0.0009765625 | |
| | | reg_lambda | 2.991485993669717 | |
| | | sampling_method | | |
| | | scale_pos_weight | | |
| | | subsample | 0.8073913094722203 | |
| | | tree_method | | |
| | | validate_parameters | | |
| | | verbosity | | |
| | |
| | </details> |
| | |
| | ### Model Plot |
| | |
| | <style>#sk-container-id-23 {color: black;}#sk-container-id-23 pre{padding: 0;}#sk-container-id-23 div.sk-toggleable {background-color: white;}#sk-container-id-23 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-23 label.sk-toggleable__label-arrow:before {content: "▸";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-23 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-23 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-23 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-23 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-23 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-23 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";}#sk-container-id-23 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-23 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-23 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-23 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-23 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-23 div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-23 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-23 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-23 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-23 div.sk-item {position: relative;z-index: 1;}#sk-container-id-23 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-23 div.sk-item::before, #sk-container-id-23 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-23 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-23 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-23 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-23 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-23 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-23 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-23 div.sk-label-container {text-align: center;}#sk-container-id-23 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-23 div.sk-text-repr-fallback {display: none;}</style><div id="sk-container-id-23" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>XGBClassifier(base_score=None, booster=None, callbacks=None,colsample_bylevel=0.9076228511174643, colsample_bynode=None,colsample_bytree=0.8045246933821307, device=None,early_stopping_rounds=None, enable_categorical=False,eval_metric=None, feature_types=None, gamma=None,grow_policy=None, importance_type=None,interaction_constraints=None, learning_rate=0.0711965541329635,max_bin=None, max_cat_threshold=None, max_cat_to_onehot=None,max_delta_step=None, max_depth=None, max_leaves=4,min_child_weight=0.27994747825685384, missing=nan,monotone_constraints=None, multi_strategy=None, n_estimators=35,n_jobs=None, num_parallel_tree=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"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-23" type="checkbox" checked><label for="sk-estimator-id-23" 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=0.9076228511174643, colsample_bynode=None,colsample_bytree=0.8045246933821307, device=None,early_stopping_rounds=None, enable_categorical=False,eval_metric=None, feature_types=None, gamma=None,grow_policy=None, importance_type=None,interaction_constraints=None, learning_rate=0.0711965541329635,max_bin=None, max_cat_threshold=None, max_cat_to_onehot=None,max_delta_step=None, max_depth=None, max_leaves=4,min_child_weight=0.27994747825685384, missing=nan,monotone_constraints=None, multi_strategy=None, n_estimators=35,n_jobs=None, num_parallel_tree=None, random_state=None, ...)</pre></div></div></div></div></div> |
| | |
| | ## Evaluation Results |
| | |
| | | Metric | Value | |
| | |----------|---------| |
| | | accuracy | 0.78 | |
| | |
| | ### Confusion Matrix |
| | |
| |  |
| | |
| | # How to Get Started with the Model |
| | |
| | [More Information Needed] |
| | |
| | # Model Card Authors |
| | |
| | Alexander Lindström |
| | |
| | # Model Card Contact |
| | |
| | You can contact the model card authors through following channels: |
| | [More Information Needed] |
| | |
| | # Citation |
| | |
| | Below you can find information related to citation. |
| | |
| | **BibTeX:** |
| | ``` |
| | [More Information Needed] |
| | ``` |
| | |
| | # precision recall f1-score support |
| | |
| | class 0 0.98 0.78 0.87 960 |
| | class 1 0.18 0.76 0.29 62 |
| | |
| | accuracy 0.78 1022 |
| | macro avg 0.58 0.77 0.58 1022 |
| | weighted avg 0.93 0.78 0.83 1022 |
| | |
| | | Metric | Value | |
| | |----------|---------| |
| | | accuracy | 0.78 | |
| | |
