Accord.NET Framework

## BinarySplit Properties |

The BinarySplit type exposes the following members.

Properties

Name | Description | |
---|---|---|

Centroids |
Gets or sets the cluster centroids.
(Inherited from KMeans.) | |

Clusters |
Gets the clusters found by K-means.
(Inherited from KMeans.) | |

ComputeCovariances |
Gets or sets whether covariance matrices for the clusters should
be computed at the end of an iteration. Default is true.
(Inherited from KMeans.) | |

ComputeError |
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.
(Inherited from KMeans.) | |

ComputeProportions |
Gets or sets whether cluster proportions
should be calculated after the learning algorithm has finished computing the clusters. Default
is false.
| |

Dimension |
Gets the dimensionality of the data space.
(Inherited from KMeans.) | |

Distance |
Gets or sets the distance function used
as a distance metric between data points.
(Inherited from KMeans.) | |

Error |
Gets the cluster distortion error after the
last call to this class' Compute methods.
(Inherited from KMeans.) | |

Iterations |
Gets the number of iterations performed in the
last call to this class' Compute methods.
(Inherited from KMeans.) | |

K |
Gets the number of clusters.
(Inherited from KMeans.) | |

MaxIterations |
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.
(Inherited from KMeans.) | |

ParallelOptions |
Gets or sets the parallelization options for this algorithm.
(Inherited from ParallelLearningBase.) | |

Token |
Gets or sets a cancellation token that can be used
to cancel the algorithm while it is running.
(Inherited from ParallelLearningBase.) | |

Tolerance |
Gets or sets the relative convergence threshold
for stopping the algorithm. Default is 1e-5.
(Inherited from KMeans.) | |

UseSeeding |
Gets or sets the strategy used to initialize the
centroids of the clustering algorithm. Default is
KMeansPlusPlus.
(Inherited from KMeans.) |

See Also