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hfREADME.md

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+---
+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).
+