Instructions to use rubanza/models-moved with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use rubanza/models-moved with Scikit-learn:
import joblib from skops.hub_utils import download download("rubanza/models-moved", "path_to_folder") model = joblib.load( "example_model_v1.pkl" ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
| library_name: sklearn | |
| license: mit | |
| tags: | |
| - sklearn | |
| - skops | |
| - tabular-classification | |
| model_format: pickle | |
| model_file: example_model_v1.pkl | |
| widget: | |
| - structuredData: | |
| Academic Pressure: | |
| - -0.04606674611568451 | |
| - -0.04606674611568451 | |
| - -0.04606674611568451 | |
| Academic Pressure_na: | |
| - 2 | |
| - 2 | |
| - 2 | |
| Age: | |
| - 1.2607895135879517 | |
| - -0.19406381249427795 | |
| - 1.584090232849121 | |
| CGPA: | |
| - 0.03309895098209381 | |
| - 0.03309895098209381 | |
| - 0.03309895098209381 | |
| CGPA_na: | |
| - 2 | |
| - 2 | |
| - 2 | |
| City: | |
| - 98 | |
| - 28 | |
| - 27 | |
| Degree: | |
| - 77 | |
| - 90 | |
| - 77 | |
| Dietary Habits: | |
| - 16 | |
| - 21 | |
| - 21 | |
| Family History of Mental Illness: | |
| - 1 | |
| - 2 | |
| - 2 | |
| Financial Stress: | |
| - 1.4229286909103394 | |
| - 1.4229286909103394 | |
| - 0.008482186123728752 | |
| Financial Stress_na: | |
| - 1 | |
| - 1 | |
| - 1 | |
| Gender: | |
| - 2 | |
| - 2 | |
| - 2 | |
| Have you ever had suicidal thoughts ?: | |
| - 1 | |
| - 1 | |
| - 2 | |
| Job Satisfaction: | |
| - 0.8020281791687012 | |
| - 1.5897727012634277 | |
| - -1.5612051486968994 | |
| Job Satisfaction_na: | |
| - 1 | |
| - 1 | |
| - 1 | |
| Name: | |
| - 79 | |
| - 269 | |
| - 90 | |
| Profession: | |
| - 46 | |
| - 15 | |
| - 56 | |
| Sleep Duration: | |
| - 30 | |
| - 20 | |
| - 30 | |
| Study Satisfaction: | |
| - 0.019511962309479713 | |
| - 0.019511962309479713 | |
| - 0.019511962309479713 | |
| Study Satisfaction_na: | |
| - 2 | |
| - 2 | |
| - 2 | |
| Work Pressure: | |
| - 1.588835597038269 | |
| - -0.7938991189002991 | |
| - -0.7938991189002991 | |
| Work Pressure_na: | |
| - 1 | |
| - 1 | |
| - 1 | |
| Work/Study Hours: | |
| - 1.2296171188354492 | |
| - 1.4891586303710938 | |
| - -1.1062564849853516 | |
| Working Professional or Student: | |
| - 2 | |
| - 2 | |
| - 2 | |
| # Model description | |
| [More Information Needed] | |
| ## Intended uses & limitations | |
| [More Information Needed] | |
| ## Training Procedure | |
| [More Information Needed] | |
| ### Hyperparameters | |
| <details> | |
| <summary> Click to expand </summary> | |
| | Hyperparameter | Value | | |
| |--------------------------|---------| | |
| | ccp_alpha | 0.0 | | |
| | class_weight | | | |
| | criterion | gini | | |
| | max_depth | | | |
| | max_features | | | |
| | max_leaf_nodes | | | |
| | min_impurity_decrease | 0.0 | | |
| | min_samples_leaf | 1 | | |
| | min_samples_split | 2 | | |
| | min_weight_fraction_leaf | 0.0 | | |
| | random_state | | | |
| | splitter | best | | |
| </details> | |
| ### Model Plot | |
| <style>#sk-container-id-2 {color: black;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 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-2 label.sk-toggleable__label-arrow:before {content: "▸";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 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-2 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-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 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-2 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-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 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-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 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-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 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-2 div.sk-text-repr-fallback {display: none;}</style><div id="sk-container-id-2" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>DecisionTreeClassifier()</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-2" type="checkbox" checked><label for="sk-estimator-id-2" class="sk-toggleable__label sk-toggleable__label-arrow">DecisionTreeClassifier</label><div class="sk-toggleable__content"><pre>DecisionTreeClassifier()</pre></div></div></div></div></div> | |
| ## Evaluation Results | |
| | Metric | Value | | |
| |----------|----------| | |
| | accuracy | 0.899751 | | |
| # How to Get Started with the Model | |
| [More Information Needed] | |
| # Model Card Authors | |
| This model card is written by following authors: | |
| [More Information Needed] | |
| # 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] | |
| ``` | |
| # citation_bibtex | |
| bibtex | |
| @inproceedings{...,year={2024}} | |
| # get_started_code | |
| import pickle | |
| with open(dtc_pkl_filename, 'rb') as file: | |
| clf = pickle.load(file) | |
| # model_card_authors | |
| Rubanza | |
| # limitations | |
| This model is not ready to be used in production. | |
| # model_description | |
| This is a random forest classifier model trained a mental health dataset. | |
| # eval_method | |
| The model is evaluated using test split, on accuracy | |