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