Clustering (version 1.7.7)

[.clustering: Filter metrics in a clustering object returning a new clustering object.

Description

Generates a new filtered clustering object.

Usage

# S3 method for clustering
[(clustering, condition = TRUE)

Arguments

clustering

The clustering object to filter.

condition

Expression to filter the clustering object.

Value

A clustering object filtered from the input parameters.

Details

This function allows you to filter the data set for a given evaluation metric. The evaluation metrics available are: Algorithm, Distance, Clusters, Data, Var, Time, Entropy, Variation_information, Precision, Recall, F_measure, Fowlkes_mallows_index, Connectivity, Dunn, Silhouette and TimeAtt.

Examples

# NOT RUN {
library(Clustering)

result <- clustering(df = Clustering::basketball, algorithm = 'clara',
min=3, max=4, metrics = c('Precision','Recall'))

result[Precision > 0.14 & Recall > 0.11]

# }