Performance evaluation of classification algorithms by k-fold and leave-one-out cross validation
作者：
Highlights：
• The definition of independence assumptions is proposed and discussed.
• The sampling distributions for k-fold and leave-one-out cross validation are derived.
• New insights in evaluating the performance of classification algorithms are provided.
摘要
•The definition of independence assumptions is proposed and discussed.•The sampling distributions for k-fold and leave-one-out cross validation are derived.•New insights in evaluating the performance of classification algorithms are provided.
论文关键词：Classification,Independence,k-Fold cross validation,Leave-one-out cross validation,Sampling distribution
论文评审过程：Received 6 November 2014, Revised 4 February 2015, Accepted 8 March 2015, Available online 17 March 2015, Version of Record 16 May 2015.
论文官网地址：https://doi.org/10.1016/j.patcog.2015.03.009
