In this we are going to implement decision tree and Ensemble methods. To predict the test data set and print out both the training accuracy results and testing accuracy results. It breaks down a Data- set into smaller and smaller subsets while at the same time an associated decision tree is incrementally developed. The final result is a tree with decision nodes and leaf nodes, training and testing accuracy score. Solving with both a logistic regression problem and classification problem using Decision Tree, Ensemble, Voting, Bagging and Random Forest.
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