hmm_svd: hmm_svd

In protHMM: Protein Feature Extraction from Profile Hidden Markov Models

hmm_svd

Description

This feature uses singular value decomposition (SVD) to reduce the dimensionality of the inputted hidden markov model matrix. SVD factorizes a matrix C of dimensions i, j to U[i, r] \times \Sigma[r, r] \times V[r, j]. The diagonal values of \Sigma are known as the singular values of matrix C, and are what are returned with this function.

Usage

hmm_svd(hmm)

Arguments

hmm	The name of a profile hidden markov model file.

Value

A vector of length 20.

References

Song, X., Chen, Z., Sun, X., You, Z., Li, L., & Zhao, Y. (2018). An Ensemble Classifier with Random Projection for Predicting Protein–Protein Interactions Using Sequence and Evolutionary Information. Applied Sciences, 8(1), 89.

Examples

h<- hmm_svd(system.file("extdata", "1DLHA2-7", package="protHMM"))

protHMM documentation built on July 9, 2023, 6:10 p.m.