Description Usage Arguments Details Value References See Also Examples

View source: R/distortionMin.R

Runs one K-means loop based on the diffusion coordinates of a data set, beginning from an initial set of cluster centers.

1 | ```
distortionMin(X, phi0, K, c0, epsilon = 0.001)
``` |

`X` |
diffusion coordinates, each row corresponds to a data point |

`phi0` |
trivial left eigenvector of Markov matrix (stationary distribution of Markov random walk) in diffusion map construction |

`K` |
number of clusters |

`c0` |
initial cluster centers |

`epsilon` |
stopping criterion for relative change in distortion |

Used by diffusionKmeans().

The returned value is a list with components

`S` |
labelling from K-means loop. n-dimensional vector with integers between 1 and K |

`c` |
K geometric centroids found by K-means |

`D` |
minimum of total distortion (loss function of K-means) found in K-means run |

`DK` |
n by k matrix of squared (Euclidean) distances from each point to every centroid |

Lafon, S., & Lee, A., (2006), IEEE Trans. Pattern Anal. and Mach. Intel., 28, 1393

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