Classifying Categorical Data Based on Adoptive Hamming Distance

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概要

• 論文の詳細を見る

• In this paper, we improve the classification performance of categorical data using an Adoptive Hamming Distance. We defined the equivalent categorical values and showed how those categorical values were searched to adopt the distance. The effectiveness of the proposed method was demonstrated using various classification examples.

• （社）電子情報通信学会の論文
• 2010-01-01

著者

• Kim Dae-won

  School Of Computer Science And Engineering Chung-ang University

• Lee Jae-sung

  School Of Computer Science And Engineering Chung-ang University

関連論文

• Fuzzy Ranking Model Based on User Preference(Natural Language Processing)
• Classifying Categorical Data Based on Adoptive Hamming Distance
• Classification Based on Predictive Association Rules of Incomplete Data

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