FLClustering-class: An S4 class to represent FLKMedoids

In Fuzzy-Logix/AdapteR: Converts R syntax to SQL to provide fast analytics using in-database C++ library DB Lytix.

Description

An S4 class to represent FLKMedoids

Arguments

object	retrieves the clustering vector
object	returns matrix of the medoids or representative objects of the clusters. If a dissimilarity matrix was given as input to pam, then a vector of numbers or labels of observations is given, else medoids is a matrix with in each row the coordinates of one medoid.
object	returns integer vector of indices giving the medoid observation numbers.
object	the objective function after the first and second step of the pam algorithm.
object	returns vector with length equal to the number of clusters, specifying which clusters are isolated clusters (L- or L*-clusters) and which clusters are not isolated.
object	returns matrix, each row gives numerical information for one cluster. These are the cardinality of the cluster (number of observations), the maximal and average dissimilarity between the observations in the cluster and the cluster's medoid, the diameter of the cluster (maximal dissimilarity between two observations of the cluster), and the separation of the cluster (minimal dissimilarity between an observation of the cluster and an observation of another cluster).
object	returns list with silhouette width information.
object	dissimilarity (maybe NULL).
object	function generating call.
object	returns a matrix containing the original or standardized data. This might be missing to save memory or when a dissimilarity matrix was given as input structure to the clustering method.
object	prints the results of pam on FL objects.
object	plots the results of pam on FL objects.
object	gives the mapping data.frame which is used in execution.

Slots

centers

A numeric vector containing the number of clusters, say k

AnalysisID

A character output used to retrieve the results of analysis

wideToDeepAnalysisID

A character string denoting the intermediate identifier during widetable to deeptable conversion.

diss

logical TRUE if dissimilarity matrix is supplied to pam

table

FLTable object given as input on which analysis is performed

results

A list of all fetched components

deeptable

A character vector containing a deeptable(either conversion from a widetable or input deeptable)

temptables

A list of temporary table names used across the results

mapTable

A character string name for the mapping table in-database if input is wide-table.

distTable

Name of the distance matrix. DistTable should contain a N x N distance matrix between all ObsID in an input FLTable.

maxit

maximal number of iterations for the FANNY algorithm.

Fuzzy-Logix/AdapteR documentation built on May 6, 2019, 5:07 p.m.