|
Title: |
Decision trees for binary classification variables grow equally with the Gini impurity measure and Pearson's chi-square test |
| |
Author: |
Johannes L. Grabmeier, Larry A. Lambe 
|
| |
Address: |
University of Applied Sciences Deggendorf, Edlmairstr. 6+8, D-94469, Deggendorf, Germany. ' Multidisciplinary Software Systems Research Corporation (MSSRC), P.O. Box 6667, Bloomingdale, IL 60108, USA |
| |
Journal: |
International Journal of Business Intelligence and Data Mining 2007 - Vol. 2, No.2 pp. 213 - 226 |
| |
Abstract: |
We show that for binary classification variables, Gini and Pearson purity measures yield exactly the same tree, provided all the other parameters of the algorithms are identical. A counter-example for ternary classification variables is given. |
| |
Keywords: |
decision trees; Gini; impurity measure; Pearson; chi-square test; entropy; binary classification; variables; contingency matrix; power series expansion; symmetric polynomials; purity measures; ternary classification; data mining. |
| |
DOI: |
10.1504/IJBIDM.2007.013938 |
| |
Purchase this Paper  Comment on the Paper
|
| |
