wehub-resource-sync
29 lines
538 B
Python
29 lines
538 B
Python
import logging
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import matplotlib.pyplot as plt
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from sklearn.datasets import make_classification
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from mla.tsne import TSNE
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logging.basicConfig(level=logging.DEBUG)
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X, y = make_classification(
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n_samples=500,
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n_features=10,
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n_informative=5,
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n_redundant=0,
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random_state=1111,
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n_classes=2,
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class_sep=2.5,
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)
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p = TSNE(2, max_iter=500)
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X = p.fit_transform(X)
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colors = ["red", "green"]
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for t in range(2):
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t_mask = (y == t).astype(bool)
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plt.scatter(X[t_mask, 0], X[t_mask, 1], color=colors[t])
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plt.show()
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