ROT
(Package: ADPclust) :
ROT bandwidth
Calculate the ROT bandwidth from either a data frame, or from p and n.
● Data Source:
CranContrib
● Keywords:
● Alias: ROT
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This function uses rho and delta (calculated from findRd()) to automaticly find clusters.
● Data Source:
CranContrib
● Keywords:
● Alias: findClusterAuto
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findCluster
(Package: ADPclust) :
User-interactive Finding Clusters
Uses f and delta (calculated from findRd()) to find clusters.
● Data Source:
CranContrib
● Keywords:
● Alias: findCluster
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adpclust
(Package: ADPclust) :
Fast Clustering Using Adaptive Density Peak Detection
Clustering of data by finding cluster centers from estimated density peaks. It is a non-iterative procedure that incorporates multivariate Gaussian density estimation. The number of clusters as well as bandwidths can either be selected by the user or selected automatically through an internal clustering criterion.
● Data Source:
CranContrib
● Keywords:
● Alias: adpclust
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AMISE
(Package: ADPclust) :
AMISE bandwidth
Calculate the AMISE bandwidth from either a data frame, or from p and n.
● Data Source:
CranContrib
● Keywords:
● Alias: AMISE
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plot.adpclust
(Package: ADPclust) :
Visualize the result of adpclust()
Depends on the settings of adpclust, draw figures showing silhouette vs. number of clusters, f vs. delta with selected centroids, and original data (projected to the first two principal components if dim > 2) colored by cluster assignments.
● Data Source:
CranContrib
● Keywords:
● Alias: plot.adpclust
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Summarizes results from adpclust function from the ADPclust package.
● Data Source:
CranContrib
● Keywords:
● Alias: summary.adpclust
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findFd
(Package: ADPclust) :
Find f(x) and delta(x) from a Data Set
This function finds f(x) and delta(x) of each point x, where f(x) is the density estimation at each point, and delta(x) measures the distance between x to the closest point y such that f(y) > f(x). The output is used in 'findCluster()' and 'findClusterAuto()'.
● Data Source:
CranContrib
● Keywords:
● Alias: findFd
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0 images
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