A Survey on Different Decision Tree Methods for Solving Classification Issues - Nirmala, V; Nithya, A (International Journal of Computer Sciences and Engineering, 2019)
Data mining has effectively and tremendously enhanced the service in diverse areas, such as health care, business analysis, and social media. It is used to extract useful information from a huge volume of data by using various techniques like pre-processing, feature extraction, feature selection, and classification. One of the important research issues of the data mining and machine learning is a classification model. This model is to learn a classifier from a given trained dataset to predict the class of test dataset. Decision trees have become one of the most well-known classification methods for extracting classification rules from data, on account of their excellent learning capability. This especially focuses on to examine the various decision tree techniques to support data mining environments. The main objective of this survey is to study different decision tree methods used for detecting and solving classification issues. Finally, comparisons are made for different decision tree techniques in data mining.