机器学习与数据挖掘 之 模型评估model evalution的方法(Holdout K-fold Cross-validation Bootstrap)
我们选择了分类器，训练了模型，那么评价模型/分类器好坏的方法有哪些呢
Holdout
Reserve some data for testing
就是划分训练集和测试集
K-fold Cross-validation
Divide samples to 𝑘 partitions, run classifier using 𝑘 − 1 partitions and test with the remaining
one. Repeat the process for all combinations of 𝑘 − 1 partitions
Bootstrap
Sample n instances with replacement as the training set, use those that is not sampled as the
testing setThis could be done using the Bagging classifier (will not be covered in tutorial)