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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Format: | Article |
Language: | English |
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Wiley
2014-01-01
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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. |
format | Article |
id | doaj-art-ca3481bc0be7493b954810622cfabcf3 |
institution | Kabale University |
issn | 1110-757X 1687-0042 |
language | English |
publishDate | 2014-01-01 |
publisher | Wiley |
record_format | Article |
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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