The train_test_split() function is used to randomly divide the sample data into the training set and the test set. Of course, it can also be divided into artificial slices.
Advantages: divide data randomly and objectively, reducing human factors
Full template:
train_X,test_X,train_y,test_y = train_test_split(train_data,train_target,test_size=0.3,random_state=5)
Parameter explanation:
train_data: sample data to be divided
train_target: the result of the sample data to be divided (label)
test_size: the ratio of test data to sample data, if integer, the sample size
random_state: Set the random number seed to ensure the same random number every time. If it is 0 or not filled, the data will be different every time
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Original link: https://blog.csdn.net/qq_36523839/article/details/80280771