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13 lines
547 B
Python
13 lines
547 B
Python
from trees.Stree import Stree
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from sklearn.datasets import make_classification
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random_state = 1
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X, y = make_classification(n_samples=1500, n_features=3, n_informative=3,
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n_redundant=0, n_repeated=0, n_classes=2, n_clusters_per_class=2,
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class_sep=1.5, flip_y=0, weights=[0.5, 0.5], random_state=random_state)
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model = Stree(random_state=random_state)
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model.fit(X, y)
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print(model)
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model.save_sub_datasets()
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print(f"Prediciting [{y[0]}] we have {model.predict(X[0, :].reshape(-1, X.shape[1]))}")
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