prismaHclust

PRISMA data for which a clustering should be calculated.

prismaData

the number of components that should be extracted.

ncomp

method

A matrix factorization $A = B C$ based on the results of hclust is constructed,
  which holds the mean feature values for each cluster in the matrix $B$
  and the indication of the cluster in the matrix $C$ for each data
  point (i.e. each data point is represented by its assigned cluster center).

The PRISMA package is capable of loading and processing huge text
    corpora processed with the sally toolbox (http://www.mlsec.org/sally/).
    sally acts as a very fast preprocessor which splits the text files into
    tokens or n-grams. These output files can then be read with the PRISMA
    package which applies testing-based token selection and has some
    replicate-aware, highly tuned non-negative matrix factorization and
    principal component analysis implementation which allows the processing of
    very big data sets even on desktop machines.

prismaHclust: Matrix Factorization Based on Hierarchical Clustering

Description

Usage

Arguments

Value

See Also

Examples