This contains various Classification models which can be used. Implemented using sklearn.
Unlike regression where aim is to predict a continuous number, here we do classification to predict a category. Classification models ->linear models like Logistic Regression, SVM -> Nonlinear ones like K-NN, Kernel SVM and Random Forests.
Here we would try to implement the following machine learning algorithms. Given Age and Salary whether or not a purson will purchase a car. Lets see which among the below model performs the best. Logistic Regression K-Nearest Neighbors (K-NN) Support Vector Machine (SVM) Kernel SVM Naive Bayes Decision Tree Classification Random Forest Classification
After testing the implementation on these algorithms. We implemented UCI- Breast cancer Dataset to find out the which model performs the best for predicting the Tumor is Malignant or benign.