Non-parametric decision trees and online HCI

Date

Authors

Schou (Sko), Torben

Gardner, Henry James

Martin, Michael

Publisher

Association for Computing Machinery (ACM)

Abstract

This paper proposes that online HCI studies (such as websurveys and remotely monitored usability tests) can benefit from statistical data analysis using modern statistical learning methods such as classification and regression trees (CARTs). Applying CART

Keywords

Keywords: Games; Non-parametric; Online studies; Parametric; Regression; Classification (of information); Forestry; Human computer interaction; Human engineering; Decision trees; Classification; Decision Making; Forestry; Information Retrieval; Regression Analysis Classification; Decision trees; Games; Non-parametric; Online studies; Parametric; Regression

URI

http://hdl.handle.net/1885/66399

Collections

ANU Research Publications

Source

Non-parametric Decision Trees for Online HC

Type

Conference paper

DOI

10.1145/2470654.2481288

Restricted until

2037-12-31

Downloads

File

Description

01_Schou (Sko)_Non-parametric_decision_trees_2013.pdf (368.35 KB)