sklearn.neighbors Module

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An sklearn.neighbors Module is a nearest neighbors system within sklearn.



References

  • (Scikit-Learn, 2017) ⇒ "sklearn.neighbors: Nearest Neighbors" http://scikit-learn.org/stable/modules/classes.html#module-sklearn.neighbors Retrieved: 2017-11-12
    • QUOTE: The sklearn.neighbors module implements the k-nearest neighbors algorithm.

      User guide: See the Nearest Neighbors section for further details.

      • neighbors.BallTree BallTree for fast generalized N-point problems
      • neighbors.DistanceMetric DistanceMetric class
      • neighbors.KDTree KDTree for fast generalized N-point problems
      • neighbors.KernelDensity([bandwidth, …]) Kernel Density Estimation
      • neighbors.KNeighborsClassifier([…]) Classifier implementing the k-nearest neighbors vote.
      • neighbors.KNeighborsRegressor([n_neighbors, …]) Regression based on k-nearest neighbors.
      • neighbors.LocalOutlierFactor([n_neighbors, …]) Unsupervised Outlier Detection using Local Outlier Factor (LOF)
      • neighbors.RadiusNeighborsClassifier([…]) Classifier implementing a vote among neighbors within a given radius
      • neighbors.RadiusNeighborsRegressor([radius, …]) Regression based on neighbors within a fixed radius.
      • neighbors.NearestCentroid([metric, …]) Nearest centroid classifier.
      • neighbors.NearestNeighbors([n_neighbors, …]) Unsupervised learner for implementing neighbor searches.
      • neighbors.kneighbors_graph(X, n_neighbors[, …]) Computes the (weighted) graph of k-Neighbors for points in X
      • neighbors.radius_neighbors_graph(X, radius) Computes the (weighted) graph of Neighbors for points in X

2016