As a supervised learning algorithm, Decision Tree is used to build a tree structure model for resolving classification and regression problems. The goal of this task is to implement the classification with Decision Tree and evaluate the classification performance with various evaluation methods.
Upload your project files in the Keshav_SDS_Project Folder.
[x] Downloading Balance Scale Data Set employed for validating the model.
[x] Splitting the "Balance Scale Data Set" into training and testing data.
[x] Building function for Decision Tree Classifier based on information gain and training the classifier on training data.
[ ] Implementing classification on testing data.
[ ] Evaluating the prediction results with evaluation methods including confusion matrix and accuracy.