python-kerasHow can I split my data into train and test sets using Python and Keras?

Using Python and Keras, you can split your data into train and test sets by using the train_test_split function from the scikit-learn library. This function takes in the data and splits it into two sets, a training set and a testing set. The code below shows an example of how to use the train_test_split function:

from sklearn.model_selection import train_test_split

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)

This code will randomly split the data into two sets, with 80% of the data in the training set and 20% in the testing set. The X and y variables represent the data and labels respectively. The test_size parameter specifies the proportion of the data that should be in the testing set. The random_state parameter is used to control the randomness of the split.

Code explanation

• X_train: This is the training set of data.
• X_test: This is the testing set of data.
• y_train: This is the training set of labels.
• y_test: This is the testing set of labels.
• test_size: This is the proportion of the data that should be in the testing set.
• random_state: This is used to control the randomness of the split.

For more information about the train_test_split function, see the scikit-learn documentation.

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