t-viSNE: Interactive Assessment and Interpretation of t-SNE Projections
https://doi.org/10.1109/TVCG.2020.2986996
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19 lines
468 B
19 lines
468 B
5 years ago
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# first line: 100
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def neighborhood_hit(X, y, k, selected=None):
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# Add 1 to k because the nearest neighbor is always the point itself
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k += 1
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y = np.array(y)
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knn = KNeighborsClassifier(n_neighbors=k)
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knn.fit(X, y)
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if selected:
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X = X[selected, :]
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neighbors = knn.kneighbors(X, return_distance=False)
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score = np.mean((y[neighbors] == np.tile(y[selected].reshape((-1, 1)), k)).astype('uint8'))
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return score
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