使用train_test_split()函数划分训练集、测试集和验证集

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python利用train_test_split进行训练集、验证集、测试集的随机划分众所周知，sklearn.model_selection.train_test_split可以实现训练集、测试集的两类的随机划分 na 以文本数据集为例阅读详情

Splitting the dataset into the Training set and Test set and validation set 6:2:2

from sklearn.cross_validation import train_test_split
X_train_vali, X_test, y_train_vali, y_test = train_test_split(X, y, test_size = 0.20, random_state = 0)
X_train, X_vali, y_train, y_vali = train_test_split(X_train_vali, y_train_vali, test_size = 0.25, random_state = 0)

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python训练集_Python 训练集、测试集以及验证集sklearn及手动切分需求目的：针对模型训练输入，按照6:2:2的比例进行训练集、测试集和验证集的划分。当前数据量约10万条。如果针对的是记录条数达上百万的数据集，可按照98:1:1的比例进行切分。方法一：切分训练集和测试集，采用机器学习包sklearn中的train_test_split()函数方法二：切分训练集、测试集以及验证集，针对dataframe手动切分方法一采用Sklearn包中的sklearn.model... 阅读详情

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