Description Usage Arguments Value See Also Examples

Binarizes a vector of real-valued data using the k-means clustering algorithm. The data is first split into 2 clusters.The values belonging to the cluster with the smaller centroid are set to 0, and the values belonging to the greater centroid are set to 1.

1 2 3 4 5 | ```
binarize.kMeans(vect,
nstart=1,
iter.max=10,
dip.test=TRUE,
na.rm=FALSE)
``` |

`vect` |
A real-valued vector to be binarized (at least 3 measurements). |

`nstart` |
The number of restarts for k-means. See |

`iter.max` |
The maximum number of iterations for k-means. See |

`dip.test` |
If set to |

`na.rm` |
If set to |

Returns an object of class `BinarizationResult`

.

`kmeans`

,
`BinarizationResult`

,
`BoolNet`

1 2 3 4 | ```
result <- binarize.kMeans(iris[,"Petal.Length"])
print(result)
plot(result, twoDimensional=TRUE)
``` |

Binarize documentation built on May 30, 2017, 8:17 a.m.

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