Project 1

Aim:-That company makes medicine for heart disease.We have to predict whether or not the patient has heart disease?We need to apply all five different machine learning models Logistic Regression, K-Nearest Neighbours Classifier,Support Vector machine, Decision Tree Classifier, Random Forest Classifier on the given dataset and check the accuracy about predicting whether or not the patient has heart disease.

Conclusion:-

From above bar graph we can see accuracy for each model.

1.For Logistic Regression,this model is give around 78.02�curacy. Which is slightly greater than svm model.

2.For K-Nearest Neighbours Classifier,this model is gives around 71.42�curacy.Which is smaller than Logistic Model

3.For Support Vector Machine,this model is gives around 79.12�curacy. The accuracy of This model is higher than all models.

4.For Decision Tree Classifier,this model is gives around 74.72�curacy.Which is slightly higher than KNN model.

5.For Random Forest Classifier,this model is gives around 78.02�curacy.Which is similar to logestic regression Model.

Based On Observation we can conclude that,Support Vector Mechine is best suitable for our data.Beacause it has maximum accuracy.