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Pushing the docs to dev/ for branch: main, commit e4fbc3735c51018a9b30c5d6c749249f83d37132
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dev/_downloads/00ae629d652473137a3905a5e08ea815/plot_iris_dtc.py

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# Plot the training points
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for i, color in zip(range(n_classes), plot_colors):
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idx = np.where(y == i)
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idx = np.asarray(y == i).nonzero()
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plt.scatter(
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X[idx, 0],
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X[idx, 1],
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dev/_downloads/036b9372e2e7802453cbb994da7a6786/plot_linearsvc_support_vectors.py

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# decision_function = np.dot(X, clf.coef_[0]) + clf.intercept_[0]
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# The support vectors are the samples that lie within the margin
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# boundaries, whose size is conventionally constrained to 1
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support_vector_indices = np.where(np.abs(decision_function) <= 1 + 1e-15)[0]
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support_vector_indices = (np.abs(decision_function) <= 1 + 1e-15).nonzero()[0]
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support_vectors = X[support_vector_indices]
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plt.subplot(1, 2, i + 1)
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