- Suppose we have a dataset where we seperate
features and target. We will split this dataset into train and test set.
from sklearn.model_selection import train_test_split
# Split the dataset into training and testing sets (test size = 20%)
x_train, x_test, y_train, y_test = train_test_split(features, target, test_size=0.2, random_state=42)
test_size: portion of total dataset that will use for validation while trainingrandom_state:
- specifying random state ensures that the random split is the same for every time.
42 is a random value, it can be any value.- if not specified, the split will be different for every time.
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