AC.index                Assignment Confidence (AC) index
Achlioptas.hclustering
                        Multiple Hierarchical clusterings using
                        Achlioptas random projections
Achlioptas.random.projection
                        Achlioptas random projection
Cluster.validity        Validity indices computation
Do.similarity.matrix    Functions to compute a pairwise similarity
                        matrix.
Generate.clusters       Multiple clusterings generation from the
                        corresponding trees
JL.predict.dim          Dimension of the subspace or the distortion
                        predicted according to the Johnson
                        Lindenstrauss lemma
Max.Expansion           Distortion measures: Max., min, and average
                        expansion and contraction
Multiple.Random.PAM     Multiple Random PAM clustering
Multiple.Random.fuzzy.kmeans
                        Multiple Random fuzzy-k-means clustering
Multiple.Random.hclustering
                        Multiple Random hierarchical clustering
Multiple.Random.kmeans
                        Multiple Random k-means clustering
Norm.hclustering        Multiple Hierarchical clusterings using Normal
                        random projections
PMO.hclustering         Multiple Hierarchical clusterings using Plus
                        Minus One (PMO) random projections
Plus.Minus.One.random.projection
                        Plus-Minus-One (PMO) random projections
RS.hclustering          Multiple Hierarchical clusterings using RS
                        random projections
Random.PAM.validity     PAM clustering and validity indices computation
                        using random projections of data
Random.fuzzy.kmeans.validity
                        Fuzzy-k-means clustering and validity indices
                        computation using random projections of data
Random.hclustering.validity
                        Random hierarchical clustering and validity
                        index computation using random projections of
                        data.
Random.kmeans.validity
                        k-means clustering and validity indices
                        computation using random projections of data
Transform.vector.to.list
                        Vector to list transformation of cluster
                        representation
Validity.indices        Function to compute the validity index of each
                        cluster.
generate.sample.h1      Two-levels hierarchical cluster generator.
generate.sample.h2      Three-level hierarchical cluster generator.
generate.sample.h3      Two-levels hierarchical cluster generator.
generate.sample0        Sample0 generator of synthetic data
generate.sample1        Sample1 generator of synthetic data
generate.sample2        Sample2 generator of synthetic data
generate.sample3        Sample3 generator of synthetic data
generate.sample4        Sample4 generator of synthetic data
generate.sample5        Sample5 generator of synthetic data
generate.sample6        Sample6 generator: multivariate normally
                        distributed data synthetic generator
generate.sample7        Sample7 generator: multivariate normally
                        distributed data synthetic generator
generate.uniform        Uniform bidimensional data generator
generate.uniform.random
                        Uniform bidimensional random data generator.
norm.random.projection
                        Normal random projections
rand.norm.generate      Random generation of normal distributed data
random.component.selection
                        Function to randomly select the indices of the
                        variables selected by the random subspace
                        projection
random.subspace         Random Subspace (RS) projections
