论文信息 - Research on grain information classification based on SVM decision tree

Research on grain information classification based on SVM decision tree

The defections of traditional support vector machine (for short SVM) are analyzed in the paper. According to the characteristics of grain information on the web, a multi-class classification method based on SVM decision tree (for short SVM-DT) is presented for grain information classification. Experiments prove that FI-Measure values for SVM-DT algorithm is superior to the traditional SVM algorithm. It is more suitable for application to grain information classification system.

Dexian Zhang | Jiajia Chai | Ruihuan Geng

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