標題: A DIAMOND method of inducing classification rules for biological data
作者: Li, Han-Lin
Huang, Yao-Huei
資訊管理與財務金融系 註:原資管所+財金所
Department of Information Management and Finance
關鍵字: DIAMOND;Cubes;Classification rules;Integer program
公開日期: 1-八月-2011
摘要: Identifying the classification rules for patients, based on a given dataset, is an important role in medical tasks. For example, the rules for estimating the likelihood of survival for patients undergoing breast cancer surgery are critical in treatment planning. Many well-known classification methods (as decision tree methods and hyper-plane methods) assume that classes can be separated by a linear function. However, these methods suffer when the boundaries between the classes are non-linear. This study presents a novel method, called DIAMOND, to induce classification rules from datasets containing non-linear interactions between the input data and the classes to be predicted. Given a set of objects with some classes, DIAMOND separates the objects into different cubes, and assigns each cube to a class. Via the unions of these cubes, DIAMOND uses mixed-integer programs to induce classification rules with better rates of accuracy, support and compact. This study uses three practical datasets (Iris flower, HSV patients, and breast cancer patients) to illustrate the advantages of DIAMOND over some current methods. (C) 2011 Published by Elsevier Ltd.
URI: http://dx.doi.org/10.1016/j.compbiomed.2011.05.002
http://hdl.handle.net/11536/20727
ISSN: 0010-4825
DOI: 10.1016/j.compbiomed.2011.05.002
期刊: COMPUTERS IN BIOLOGY AND MEDICINE
Volume: 41
Issue: 8
起始頁: 587
結束頁: 599
顯示於類別:期刊論文


文件中的檔案:

  1. 000294098800002.pdf