High-Speed Learning of Support Vector Machine by Divide and Conquer Method

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  • 分割統治による Support Vector Machine の学習の高速化
  • ブンカツ トウチ ニ ヨル Support Vector Machine ノ ガクシュウ ノ コウソクカ

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Abstract

Item Response Theory (IRT) is a method to analyze test and test items with assumpitions on the mathematical relationship between abilities and item responses. IRT is used for developing and refining test items in many fields of education. In this work, we carried out an IRT analysis by using data obtained from two types of programming tests. We applied the two parameter logistic model with item parameters aj and bj. The item parameter aj represents the discrimination power of the jth test item, and bj estimates ability, and this is caused partially by the insufficient number of test items.

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