2009Computer Engineering and Applications JournalRequires access

Information granularity,information entropy and decision tree

Junhai Zhai, Xizhao Wang, Sufang Zhang

Open publisher page 1 citations

Abstract

The information entropy between coarse granularity and fine granularity is comparatively studied,the influence on decision tree caused by coarse granularity and fine granularity is investigated,and the conclusion is provided that the information entropy under coarse granularity is not less than the one under fine granularity.It is shown that the decision tree generated by selecting the expanded attribute under fine granularity is better than the one under coarse granularity.

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What this paper is about

The information entropy between coarse granularity and fine granularity is comparatively studied,the influence on decision tree caused by coarse granularity and fine granularity is investigated,and the conclusion is provided that the information entropy under coarse granularity is not less than the one under fine granularity.It is shown that the decision tree generated by selecting the expanded attribute under fine granularity is better than the one under coarse granularity.

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Available abstract

The information entropy between coarse granularity and fine granularity is comparatively studied,the influence on decision tree caused by coarse granularity and fine granularity is investigated,and the conclusion is provided that the information entropy under coarse granularity is not less than the one under fine granularity.It is shown that the decision tree generated by selecting the expanded attribute under fine granularity is better than the one under coarse granularity.

Key concepts: Granularity, Entropy (arrow of time), Computer science, Data mining, Decision tree, Mathematics, Theoretical computer science, Physics

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