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--- |
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library_name: sklearn |
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tags: |
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- sklearn |
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- skops |
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- tabular-classification |
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model_format: pickle |
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model_file: model1.pkl |
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widget: |
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structuredData: |
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Age at enrollment: |
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- 20 |
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- 19 |
|
- 19 |
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Application mode: |
|
- 8 |
|
- 6 |
|
- 1 |
|
Application order: |
|
- 5 |
|
- 1 |
|
- 5 |
|
Course: |
|
- 2 |
|
- 11 |
|
- 5 |
|
Curricular units 1st sem (approved): |
|
- 0 |
|
- 6 |
|
- 0 |
|
Curricular units 1st sem (credited): |
|
- 0 |
|
- 0 |
|
- 0 |
|
Curricular units 1st sem (enrolled): |
|
- 0 |
|
- 6 |
|
- 6 |
|
Curricular units 1st sem (evaluations): |
|
- 0 |
|
- 6 |
|
- 0 |
|
Curricular units 1st sem (grade): |
|
- 0.0 |
|
- 14.0 |
|
- 0.0 |
|
Curricular units 1st sem (without evaluations): |
|
- 0 |
|
- 0 |
|
- 0 |
|
Curricular units 2nd sem (approved): |
|
- 0 |
|
- 6 |
|
- 0 |
|
Curricular units 2nd sem (credited): |
|
- 0 |
|
- 0 |
|
- 0 |
|
Curricular units 2nd sem (enrolled): |
|
- 0 |
|
- 6 |
|
- 6 |
|
Curricular units 2nd sem (evaluations): |
|
- 0 |
|
- 6 |
|
- 0 |
|
Curricular units 2nd sem (grade): |
|
- 0.0 |
|
- 13.666666666666666 |
|
- 0.0 |
|
Curricular units 2nd sem (without evaluations): |
|
- 0 |
|
- 0 |
|
- 0 |
|
Daytime/evening attendance: |
|
- 1 |
|
- 1 |
|
- 1 |
|
Debtor: |
|
- 0 |
|
- 0 |
|
- 0 |
|
Displaced: |
|
- 1 |
|
- 1 |
|
- 1 |
|
Educational special needs: |
|
- 0 |
|
- 0 |
|
- 0 |
|
Father's occupation: |
|
- 10 |
|
- 4 |
|
- 10 |
|
Father's qualification: |
|
- 10 |
|
- 3 |
|
- 27 |
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GDP: |
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- 1.74 |
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- 0.79 |
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- 1.74 |
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Gender: |
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- 1 |
|
- 1 |
|
- 1 |
|
Inflation rate: |
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- 1.4 |
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- -0.3 |
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- 1.4 |
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International: |
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- 0 |
|
- 0 |
|
- 0 |
|
Marital status: |
|
- 1 |
|
- 1 |
|
- 1 |
|
Mother's occupation: |
|
- 6 |
|
- 4 |
|
- 10 |
|
Mother's qualification: |
|
- 13 |
|
- 1 |
|
- 22 |
|
Nacionality: |
|
- 1 |
|
- 1 |
|
- 1 |
|
Previous qualification: |
|
- 1 |
|
- 1 |
|
- 1 |
|
Scholarship holder: |
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- 0 |
|
- 0 |
|
- 0 |
|
Tuition fees up to date: |
|
- 1 |
|
- 0 |
|
- 0 |
|
Unemployment rate: |
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- 10.8 |
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- 13.9 |
|
- 10.8 |
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--- |
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# Model description |
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[More Information Needed] |
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## Intended uses & limitations |
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[More Information Needed] |
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## Training Procedure |
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[More Information Needed] |
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### Hyperparameters |
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<details> |
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<summary> Click to expand </summary> |
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| Hyperparameter | Value | |
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|--------------------------|---------| |
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| bootstrap | True | |
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| ccp_alpha | 0.0 | |
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| class_weight | | |
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| criterion | gini | |
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| max_depth | | |
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| max_features | sqrt | |
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| max_leaf_nodes | | |
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| max_samples | | |
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| min_impurity_decrease | 0.0 | |
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| min_samples_leaf | 1 | |
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| min_samples_split | 2 | |
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| min_weight_fraction_leaf | 0.0 | |
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| n_estimators | 100 | |
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| n_jobs | | |
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| oob_score | False | |
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| random_state | | |
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| verbose | 0 | |
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| warm_start | False | |
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</details> |
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### Model Plot |
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<style>#sk-container-id-4 {color: black;background-color: white;}#sk-container-id-4 pre{padding: 0;}#sk-container-id-4 div.sk-toggleable {background-color: white;}#sk-container-id-4 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-4 label.sk-toggleable__label-arrow:before {content: "▸";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-4 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-4 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-4 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-4 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-4 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-4 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";}#sk-container-id-4 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-4 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-4 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-4 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-4 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-4 div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-4 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-4 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-4 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-4 div.sk-item {position: relative;z-index: 1;}#sk-container-id-4 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-4 div.sk-item::before, #sk-container-id-4 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-4 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-4 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-4 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-4 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-4 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-4 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-4 div.sk-label-container {text-align: center;}#sk-container-id-4 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-4 div.sk-text-repr-fallback {display: none;}</style><div id="sk-container-id-4" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>RandomForestClassifier()</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-4" type="checkbox" checked><label for="sk-estimator-id-4" class="sk-toggleable__label sk-toggleable__label-arrow">RandomForestClassifier</label><div class="sk-toggleable__content"><pre>RandomForestClassifier()</pre></div></div></div></div></div> |
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## Evaluation Results |
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| Metric | Value | |
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|----------|---------| |
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| accuracy | 0.9041 | |
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| roc_auc | 0.9157 | |
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# How to Get Started with the Model |
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[More Information Needed] |
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# Model Card Authors |
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This model card is written by following authors: |
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[More Information Needed] |
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# Model Card Contact |
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You can contact the model card authors through following channels: |
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[More Information Needed] |
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# Citation |
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Below you can find information related to citation. |
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**BibTeX:** |
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``` |
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[More Information Needed] |
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``` |
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# model_description |
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This is a RandomForest Classifier trained on student academic performance data. |
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# limitations |
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This model is trained for educational purposes. |
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# Confusion Matrix |
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