Data Preprocessing-Based Comparative Study on Decision Tree Induction Algorithm

Abstract

Data preprocessing is an important step in the knowledge discover process and quality decisions such as, real-world data which tend to be incomplete, noisy and inconsistent data. The system uses the discretization and concept hierarchy generation, that transforms the numeric data to categorical values in the data preprocessing techniques.Moreover, this paper addresses the speed and scalability issues by proposing a data classification method which attributes selection measure and the induction of decision tree .Myanmar is a country that its’ economy is based on agriculture. Crop production plays an important role in the session of agriculture. So, this system provides business application areas for crop information. This system compares decision tree generation time and the accuracy of the data preprocessing with and without preprocessing data.