Evaluation of Sampling and Cross-Validation Tuning Strategies for Regional-Scale Machine Learning Cl
比较了不一样抽样方法（随机，分层等比随机，分层不等比随机，人为），不一样交叉验证方法（k折，留一法，蒙特卡洛），不一样样本范围大小的效果，最后都是用SVM分类方法
结果是k折验证最好，人为选择样本最差。小范围小样本的效果和分布普遍的样本的效果差很少，说明了若是取样困难，小样本也是能用的
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相关文章
- 1. Evaluation of Sampling Methods for Scatterplots
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