Mkdh321 asked in 社會與文化語言 · 8 years ago





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As technology developed, the ordinal data is everywhere in everyday life and increasingly important, especially on the analysis of disease data and image retrieval more important.

本文次序型樣本在特徵空間中成為有效的次序且有部份擾動點干擾下,以成對樣本的角度,利用不同懲罰係數的支持向量機(Support Vector Machine, (SVM))結合累積羅吉斯模型(Cumulative logit model, (CLM))來分析次序型資料,並說明如何決定出次序迴歸演算法的參數。

In this paper, the ordinal samples in the feature space with effective order and part of the disturbance point interference…the point of view of the paired data,…we use different coefficients of punishment Support Vector Machine (SVM) to combine the Cumulative logit model (CLM) to analyze the ordinal data (order-type information), and explain how to determine the parameters of the ordinal regression algorithm.

再介紹處理SVM最常用的依序最佳化演算法(Sequential Minimal Optimization, (S


We will explain the deal with the most commonly used SVM optimization algorithm:Sequential Minimal Optimization (SMO), and the Maximum-Gain Working Set Selection for the Single sequential minimal optimization algorithm.


The last experiment to the order of the average error rate for the general data set to compare their advantages and disadvantages, and explains how to ordinal regression algorithms used in image retrieval.



次序型資料: 是表示資料類別是有次序,如 疾病的 第一期,第二期....,因此叫次序型資料

原本GOOGLE是用order data、Order sample,可是我不太確定他的意思,

所以我都用ordinal data,ordinal sample,(因诙次序迴歸的英文的ordinal regression)。



, angle, in paired samples,-->這我不太了解

1 Answer

  • 8 years ago
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    With advances in technology, order data is everywhere, and increasingly important in daily life, particularly in the areas of disease data analysis and image retrieval is of even more importance on.Order sample in this article in the feature space into an effective point of order, and there are some disturbances under the disturbance, angle, in paired samples, using different penalty coefficient of support vector machine "Support Vector Machine, (SVM)" combined cumulative d. Rogers model "Cumulative logit model, (CLM)" to analyze order data, and explains how to determine order regression algorithm parameters.In dealing with most common order optimization algorithm for SVM "Sequential Minimal Optimization, (sMO) "and this order optimization algorithm for the maximum gain of a single variable.Final experiments to general average error rates in the order of the data set to compare their advantages and disadvantages, and instructions on how to apply order regression algorithm in image retrieval.

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