estimateDimension

A prismaData object loaded via loadPrismaData

prismaData

Error probability for confidence intervals

alpha

The number of scrambled samples that should be used to estimate the
 noise model. NULL means to use the complete data set.

nScrambleSamples

Matrix factorization methods compress the original data matrix \(A \in
 R^{f,N}\) with \(f\) features and \(N\) samples into two parts,
 namely \(A = B C\) with \(B \in R^{f,k}, C\in R^{k,
 N}\). The function estimateDimension estimates \(k\) based on a noise
 model estimated from a scrambled version of the original data matrix.

Loads and processes 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.

estimateDimension: Estimate Inner Dimension

Description

Usage

Arguments

Value

References

Examples