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# Getting data |
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from sklearn.datasets import load_breast_cancer |
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cancer = load_breast_cancer() |
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classes=cancer.target_names |
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X = cancer.data |
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y = cancer.target |
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# Importing PCA visualizer |
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from yellowbrick.model_selection import ValidationCurve |
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# Importing RandomForestClassifier |
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from sklearn.ensemble import RandomForestClassifier |
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# Creating the validation curve |
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import numpy as np |
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visualizer = ValidationCurve(RandomForestClassifier(), |
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param_name="max_depth", n_jobs=-1, |
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param_range=np.arange(1, 11), |
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cv=10, scoring="accuracy") |
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visualizer.fit(X, y) |
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# Saving plot in PNG format |
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visualizer.show(outpath="Validation_Curve.png") |