A study on the selection error rate of classification algorithms evaluated by k-fold cross validation.

碩士 === 國立成功大學 === 資訊管理研究所 === 102 === The performance of a classification algorithm is generally evaluated by K-fold cross validation to find the one that has the highest accuracy. Then the model induced from all available data by the best classification algorithm, called full sample model, is used...

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Bibliographic Details
Main Authors: Chiao-YingLin, 林巧盈
Other Authors: Tzu-Tsung Wong
Format: Others
Language:zh-TW
Published: 2014
Online Access:http://ndltd.ncl.edu.tw/handle/23699989925707105417

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