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A machine learning model using Support Vector Machine classification to predict chances of an individual having a heart attack based on features like age, sex, cholestrol, blood pressure, chest pain, heart beat etc.

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HeartAttackPredictor

A machine learning model using Support Vector Machine classification to predict chances of an individual having a heart attack based on features like age, sex, cholestrol, blood pressure, chest pain, heart beat etc.

Requirements

  1.Numpy
  2.Pandas
  3.Sckitlearn   

Training Data

Data used for training heart.csv from Kaggle

Training Features

1. age	
2. sex
3. chest_pain_type
4. rest_blood_pressure
5. cholestrol	
6. fasting_blood_sugar
7. resting_ecg_result
8. max_heart_rate
9. exercise_induced_angina
10. oldpeak

Training Against

 11. output(1 for cancer, 0 for no cancer)

Models Used

 1. Support Vector Machine
 2. Logistic Regression

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A machine learning model using Support Vector Machine classification to predict chances of an individual having a heart attack based on features like age, sex, cholestrol, blood pressure, chest pain, heart beat etc.

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