Click or drag to resize
Accord.NET (logo)

KMeans Properties

The KMeans type exposes the following members.

Public propertyCentroids
Gets or sets the cluster centroids.
Public propertyClusters
Gets the clusters found by K-means.
Public propertyComputeCovariances
Gets or sets whether covariance matrices for the clusters should be computed at the end of an iteration. Default is true.
Public propertyComputeError
Gets or sets whether the clustering distortion error (the average distance between all data points and the cluster centroids) should be computed at the end of the algorithm. The result will be stored in Error. Default is true.
Public propertyDimension
Gets the dimensionality of the data space.
Public propertyDistance
Gets or sets the distance function used as a distance metric between data points.
Public propertyError
Gets the cluster distortion error after the last call to this class' Compute methods.
Public propertyIterations
Gets the number of iterations performed in the last call to this class' Compute methods.
Public propertyK
Gets the number of clusters.
Public propertyMaxIterations
Gets or sets the maximum number of iterations to be performed by the method. If set to zero, no iteration limit will be imposed. Default is 0.
Public propertyParallelOptions
Gets or sets the parallelization options for this algorithm.
(Inherited from ParallelLearningBase.)
Public propertyToken
Gets or sets a cancellation token that can be used to cancel the algorithm while it is running.
(Inherited from ParallelLearningBase.)
Public propertyTolerance
Gets or sets the relative convergence threshold for stopping the algorithm. Default is 1e-5.
Public propertyUseSeeding
Gets or sets the strategy used to initialize the centroids of the clustering algorithm. Default is KMeansPlusPlus.
See Also