The Application of Decision Tree Method for Data Mining

Abstract

The study showcases the impact of data mining considering the application of decision trees that helps to develop data from large number of datasets. Linear data set has been generated through the model of decision trees. Secondary data collection method has been selected in this study with inductive approach. Cross sectional research design has been used in this study to derived insight of the subject of the study. Themes are developed using the peer reviewed journals published after 2019 and secondary collected data has been interpreted in this study to meet the goal of the subject. Implications of data mining including decision trees and decision rules in different field have been discussed over here with positive perspective approach. Customization of data mining in creativity also has been focused here. Different types of decision trees methods have been depicted here with comparison vision. Advantages and disadvantages of decision trees also have been discussed over here to evaluate the actual impact of application of decision trees in data mining. Interpretation of results also has been depicted here to analyse the consequences of decision trees in data mining to conclude the study with informative justification.