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Created August 17, 2020 22:25
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block1.python
# classification dataset
from sklearn.datasets import make_classification
# define dataset
X_clf, y_clf = make_classification(n_samples=1000, n_features=8, n_informative=3, n_redundant=5, random_state=1)
# summarize the dataset
print(X_clf.shape, y_clf.shape)
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