本文深入探讨了机器学习中训练集和测试集的作用。训练集用于构建模型，包含x_train和y_train，分别代表特征数据和对应标签。测试集则用于评估模型性能，包括x_test和y_test，同样为特征数据及其标签。理解这些概念对于有效应用机器学习至关重要。
The training set is a subset of the data set used to train a model.
x_train is the training data set.
y_train is the set of labels to all the data in x_train.
The test set is a subset of the data set that you use to test your model after the model has gone through initial vetting by the validation set.
x_test is the test data set.
y_test is the set of labels to all the data in x_test.
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