`pipeline_optimizer.fit(X_train, y_train)`
2191 and (train_size <= 0 or train_size >= 1) 2192 ): -> 2193 raise ValueError( 2194 "train_size={0} should be either positive and smaller" 2195 " than the number of samples {1} or a float in the "
ValueError: train_size=19864 should be either positive and smaller than the number of samples 19864 or a float in the (0, 1) range
how do i fix this
`X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)`
ive try changing the test size and it dont work