/Heart-Disease-prediction

Heart disease prediction was done using two model 1: logistic regression 2: Random Forest Classifier

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Heart-Disease-prediction

Here two model was build in order to predict the heart disease from a given dataset ie. Logistic Regression 2nd: Random Forest Classifier . First models were build without tunning hyperparameters and later on models were build with tunned hyperparameters then the results were monitered.

The technique of Hyperparameter optimization and Feature Selection did increase the accuracy of my model.

Before Hyperparameter optimation and Feature Selection

Accuracy for: Logistic Regression : 0.84 Random Forest Classifier : 84.056603773584

After Hyperparameter optimation and Feature Selection

Accuracy for: Logistic Regression : 0.86 Random Forest Classifier : 85