Decision Tree Classification Model for Popularity Forecast of Chinese Colleges

Prospective students generally select their preferred college on the basis of popularity. Thus, this study uses survey data to build decision tree models for forecasting the popularity of a number of Chinese colleges in each district. We first extract a feature called “popularity change ratio” from...

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Main Authors: Xiangxiang Zeng, Sisi Yuan, You Li, Quan Zou
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2014/675806
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author Xiangxiang Zeng
Sisi Yuan
You Li
Quan Zou
author_facet Xiangxiang Zeng
Sisi Yuan
You Li
Quan Zou
author_sort Xiangxiang Zeng
collection DOAJ
description Prospective students generally select their preferred college on the basis of popularity. Thus, this study uses survey data to build decision tree models for forecasting the popularity of a number of Chinese colleges in each district. We first extract a feature called “popularity change ratio” from existing data and then use a simplified but efficient algorithm based on “gain ratio” for decision tree construction. The final model is evaluated using common evaluation methods. This research is the first of its type in the educational field and represents a novel use of decision tree models with time series attributes for forecasting the popularity of Chinese colleges. Experimental analyses demonstrated encouraging results, proving the practical viability of the approach.
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institution Kabale University
issn 1110-757X
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publishDate 2014-01-01
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series Journal of Applied Mathematics
spelling doaj-art-ca3481bc0be7493b954810622cfabcf32025-02-03T06:14:17ZengWileyJournal of Applied Mathematics1110-757X1687-00422014-01-01201410.1155/2014/675806675806Decision Tree Classification Model for Popularity Forecast of Chinese CollegesXiangxiang Zeng0Sisi Yuan1You Li2Quan Zou3Department of Computer Science, Xiamen University, Xiamen, Fujian 361005, ChinaDepartment of Computer Science, Xiamen University, Xiamen, Fujian 361005, ChinaDepartment of Computer Science, Xiamen University, Xiamen, Fujian 361005, ChinaDepartment of Computer Science, Xiamen University, Xiamen, Fujian 361005, ChinaProspective students generally select their preferred college on the basis of popularity. Thus, this study uses survey data to build decision tree models for forecasting the popularity of a number of Chinese colleges in each district. We first extract a feature called “popularity change ratio” from existing data and then use a simplified but efficient algorithm based on “gain ratio” for decision tree construction. The final model is evaluated using common evaluation methods. This research is the first of its type in the educational field and represents a novel use of decision tree models with time series attributes for forecasting the popularity of Chinese colleges. Experimental analyses demonstrated encouraging results, proving the practical viability of the approach.http://dx.doi.org/10.1155/2014/675806
spellingShingle Xiangxiang Zeng
Sisi Yuan
You Li
Quan Zou
Decision Tree Classification Model for Popularity Forecast of Chinese Colleges
Journal of Applied Mathematics
title Decision Tree Classification Model for Popularity Forecast of Chinese Colleges
title_full Decision Tree Classification Model for Popularity Forecast of Chinese Colleges
title_fullStr Decision Tree Classification Model for Popularity Forecast of Chinese Colleges
title_full_unstemmed Decision Tree Classification Model for Popularity Forecast of Chinese Colleges
title_short Decision Tree Classification Model for Popularity Forecast of Chinese Colleges
title_sort decision tree classification model for popularity forecast of chinese colleges
url http://dx.doi.org/10.1155/2014/675806
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