Classification of Import Market by using CART Algorithm

Abstract

The goal of this paper is to classify Import Market data to support the decision makers for Import Market. The main task performed in this system is used Classification and Regression Tree (CART) Algorithm. In this paper, there are two mains phases. In the training phase, attributes are analyzed by impurity function (Gini index) method. The impurity function (Gini index) measured method is used which computes the maximally reduce impurity of each attribute for the training data set. By using the training data, this system will construct the model or classifier to generate the form of classification rules. In the testing phase, calculate the accuracy of the classification rules by using the test data. This system will construct the decision tree according to the new product data and produces the result that is decision for how to investment.