| | --- |
| | library_name: sklearn |
| | tags: |
| | - random-forest |
| | - stroke-prediction |
| | - sklearn |
| | pipeline_tag: tabular-classification |
| | license: mit |
| | --- |
| | |
| |
|
| | # Stroke Prediction Random Forest Model |
| |
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| | This project uses a Random Forest model to predict the risk of strokes based on user input features. The model has been deployed on Hugging Face for seamless integration. |
| |
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| | ## Features |
| | - Predicts the likelihood of a stroke based on various health parameters. |
| | - Fast and efficient model, hosted on Hugging Face. |
| |
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| | ## Input Features |
| | The model expects the following inputs: |
| | - `age`: Patient's age (numeric) |
| | - `age_group`: Patients age group child(Less than 18 ),Young Adult (18-34 ), Adult (35-59 ), Senior (60 and over ) |
| | - `hypertension`: 1 if the patient has hypertension, else 0 |
| | - `heart_disease`: 1 if the patient has heart disease, else 0 |
| | - `avg_glucose_level`: Average glucose level in the blood |
| | - `bmi`: Body Mass Index |
| | - `gender`: Male/Female/Other |
| | - `ever_married`: Yes/No |
| | - `work_type`: Type of work (e.g., Private, Self-employed, never_worked) |
| | - `Residence_type`: Urban/Rural |
| | - `smoking_status`: Smoking habits (e.g., never smoked, formerly smoked) |
| |
|
| | ## Model Deployment |
| | The model has been deployed on the [Hugging Face Hub](https://huggingface.co). You can access it via my repo [Random Forest Model for Stroke Prediction](https://huggingface.co/Asiya-Mohammed/random-forest-model). |
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