|
--- |
|
library_name: sklearn |
|
tags: |
|
- random-forest |
|
- stroke-prediction |
|
- sklearn |
|
pipeline_tag: tabular-classification |
|
license: mit |
|
--- |
|
|
|
|
|
# Stroke Prediction Random Forest Model |
|
|
|
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. |
|
|
|
## Features |
|
- Predicts the likelihood of a stroke based on various health parameters. |
|
- Fast and efficient model, hosted on Hugging Face. |
|
|
|
## 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). |
|
|
|
|
