The Use of Regression Analysis for Evaluating the Outcomes of Decision Tree Techniques

Student: Klementev Aleksandr

Educational Programme: Applied Methods of Social Analysis of Markets (Master)

Final Grade: 8

Year of Graduation: 2019

This paper aims to assess the effectiveness decision-tree models for solving typical sociological tasks. The paper assesses the predictive power of statistical models built on RLMS data using classical (CHAID, CART) and modern (J48, C50, LMT, M5P) decision trees algorithms in comparison to models built using regression analysis. The author concludes that tree models have predictive power that is similar to regression models, while offering a number of additional advantages, which can be used to identify new and relevant sociological insights in the data. The paper proposes a strategy for incorporating decision trees into data analysis as a complimentary tool alongside regressions and outlines directions for further research.

Full text (added May 21, 2019)

Student Theses at HSE must be completed in accordance with the University Rules and regulations specified by each educational programme.

Summaries of all theses must be published and made freely available on the HSE website.

The full text of a thesis can be published in open access on the HSE website only if the authoring student (copyright holder) agrees, or, if the thesis was written by a team of students, if all the co-authors (copyright holders) agree. After a thesis is published on the HSE website, it obtains the status of an online publication.

Student theses are objects of copyright and their use is subject to limitations in accordance with the Russian Federation’s law on intellectual property.

In the event that a thesis is quoted or otherwise used, reference to the author’s name and the source of quotation is required.

Search all student theses