Regression Analyses or Decision Trees? Cover Image

Regression Analyses or Decision Trees?
Regression Analyses or Decision Trees?

Author(s): Burcu Kocarık Gacar, İpek Deveci Kocakoç
Subject(s): Methodology and research technology
Published by: Celal Bayar Üniversitesi Sosyal Bilimler Enstitüsü
Keywords: Regression; Logistic Regression; Classification and Regression; Trees; Decision Trees;

Summary/Abstract: Decision tree algorithm is an important classification method in data mining techniques. A decision tree creates classification and regression models like a tree that has a root node, branches, and leaf nodes. Logistic regression which is an alternative method to regression analysis when the dependent variable is a dichotomy, is another technique used for classification purposes. Within the scope of this research, logistic regression, linear regression, classification tree, and regression tree were applied on the same data set. This study explores the most important variables determining the house price by using these four methods. Models’ performances and predictive powers were compared and the best model is determined. This comparison was performed using 414 real estate data on 5 independent variables and the dependent variable is house price. The findings showed that the classification tree model for real estate valuation data performs better than standard approaches.

  • Issue Year: 18/2020
  • Issue No: 04
  • Page Range: 251-260
  • Page Count: 10
  • Language: English