sklearn.neighbors#
The k-nearest neighbors algorithms.
User guide. See the Nearest Neighbors section for further details.
BallTree for fast generalized N-point problems |
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KDTree for fast generalized N-point problems |
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Classifier implementing the k-nearest neighbors vote. |
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Regression based on k-nearest neighbors. |
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Transform X into a (weighted) graph of k nearest neighbors. |
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Kernel Density Estimation. |
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Unsupervised Outlier Detection using the Local Outlier Factor (LOF). |
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Nearest centroid classifier. |
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Unsupervised learner for implementing neighbor searches. |
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Neighborhood Components Analysis. |
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Classifier implementing a vote among neighbors within a given radius. |
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Regression based on neighbors within a fixed radius. |
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Transform X into a (weighted) graph of neighbors nearer than a radius. |
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Compute the (weighted) graph of k-Neighbors for points in X. |
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Compute the (weighted) graph of Neighbors for points in X. |
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Sort a sparse graph such that each row is stored with increasing values. |