Clustering (version 1.7)

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

Description

Generates a new clustering object containing the metrics that passed the filter specified.

Usage

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

Arguments

clustering

The clustering object to filter.

condition

Expression to filter the clustering object

Details

This function allows you to filter the data set for a given evaluation metric. The evaluation metrics available are: Algorithm, Distance, Clusters, Dataset, Ranking, timeExternal, entropy, variation_information, precision, recall, f_measure, fowlkes_mallows_index, connectivity, dunn, silhouette, timeInternal.

Examples

# NOT RUN {
library(Clustering)

result <- clustering(package = 'clusterr', df = Clustering::basketball, min=3, max=4)

result[precision > 0.14 & dunn > 0.11]

# }