17 lines
510 B
Python
17 lines
510 B
Python
import numpy as np
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from sklearn.datasets import make_classification
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from sklearn.model_selection import train_test_split
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def generate_dataset():
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x, y = make_classification(n_samples=500, n_features=2, n_redundant=0,
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n_informative=2, random_state=0, n_clusters_per_class=1)
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random = np.random.RandomState(2)
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x += 2.5 * random.uniform(size=x.shape)
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return x, y
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def split_dataset(x, y):
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return train_test_split(
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x, y, test_size=.05, random_state=42)
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