R: Non-Negative Tensor Decomposition

nnTensor-package {nnTensor}

R Documentation

Non-Negative Tensor Decomposition

Description

Some functions for performing non-negative matrix factorization, non-negative CANDECOMP/PARAFAC (CP) decomposition, non-negative Tucker decomposition, and generating toy model data. See Andrzej Cichock et al (2009) and the reference section of GitHub README.md <https://github.com/rikenbit/nnTensor>, for details of the methods.

Details

The DESCRIPTION file:

Package:	nnTensor
Type:	Package
Title:	Non-Negative Tensor Decomposition
Version:	1.3.0
Authors@R:	c(person("Koki", "Tsuyuzaki", role = c("aut", "cre"), email = "k.t.the-answer@hotmail.co.jp"), person("Itoshi", "Nikaido", role = "aut"))
Depends:	R (>= 3.4.0)
Imports:	methods, MASS, fields, rTensor, plot3D, tagcloud, ggplot2
Suggests:	knitr, rmarkdown, testthat, dplyr
Description:	Some functions for performing non-negative matrix factorization, non-negative CANDECOMP/PARAFAC (CP) decomposition, non-negative Tucker decomposition, and generating toy model data. See Andrzej Cichock et al (2009) and the reference section of GitHub README.md <https://github.com/rikenbit/nnTensor>, for details of the methods.
License:	MIT + file LICENSE
URL:	https://github.com/rikenbit/nnTensor
VignetteBuilder:	knitr
Author:	Koki Tsuyuzaki [aut, cre], Itoshi Nikaido [aut]
Maintainer:	Koki Tsuyuzaki <k.t.the-answer@hotmail.co.jp>

Index of help topics:

GabrielNMF              Gabriel-type Bi-Cross-Validation for
                        Non-negative Matrix Factorization
NMF                     Non-negative Matrix Factorization Algorithms
                        (NMF)
NMTF                    Non-negative Matrix Tri-Factorization
                        Algorithms (NMTF)
NTD                     Non-negative Tucker Decomposition Algorithms
                        (NTD)
NTF                     Non-negative CP Decomposition Algorithms (NTF)
jNMF                    Joint Non-negative Matrix Factorization
                        Algorithms (jNMF)
kFoldMaskTensor         Mask tensors generator to perform k-fold cross
                        validation
nnTensor-package        Non-Negative Tensor Decomposition
plot.NMF                Plot function of the result of NMF function
plotTensor2D            Plot function for visualization of matrix data
                        structure
plotTensor3D            Plot function for visualization of tensor data
                        structure
recTensor               Tensor Reconstruction from core tensor (S) and
                        factor matrices (A)
siNMF                   Simultaneous Non-negative Matrix Factorization
                        Algorithms (siNMF)
toyModel                Toy model data for using NMF, NTF, and NTD

Author(s)

Maintainer: NA

References

Andrzej CICHOCK, et. al., (2009). Nonnegative Matrix and Tensor Factorizations. John Wiley & Sons, Ltd

Keigo Kimura, (2017). A Study on Efficient Algorithms for Nonnegative Matrix/Tensor Factorization. Hokkaido University Collection of Scholarly and Academic Papers

Andrzej CICHOCKI et. al., (2007). Non-negative Tensor Factorization using Alpha and Beta Divergence. IEEE ICASSP 2007

Anh Huy PHAN et. al., (2008). Multi-way Nonnegative Tensor Factorization Using Fast Hierarchical Alternating Least Squares Algorithm (HALS). NOLTA2008

Andrzej CICHOCKI et. al., (2008). Fast Local Algorithms for Large Scale Nonnegative Matrix and Tensor Factorizations. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

Yong-Deok Kim et. al., (2007). Nonnegative Tucker Decomposition. IEEE Conference on Computer Vision and Pattern Recognition

Yong-Deok Kim et. al., (2008). Nonneegative Tucker Decomposition With Alpha-Divergence. IEEE International Conference on Acoustics, Speech and Signal Processing

Anh Huy Phan, (2008). Fast and efficient algorithms for nonnegative Tucker decomposition. Advances in Neural Networks - ISNN2008

Anh Hyu Phan et. al. (2011). Extended HALS algorithm for nonnegative Tucker decomposition and its applications for multiway analysis and classification. Neurocomputing

Jean-Philippe Brunet. et. al., (2004). Metagenes and molecular pattern discovery using matrix factorization. PNAS

Xiaoxu Han. (2007). CANCER MOLECULAR PATTERN DISCOVERY BY SUBSPACE CONSENSUS KERNEL CLASSIFICATION

Attila Frigyesi. et. al., (2008). Non-Negative Matrix Factorization for the Analysis of Complex Gene Expression Data: Identification of Clinically Relevant Tumor Subtypes. Cancer Informatics

Haesun Park. et. al., (2019). Lecture 3: Nonnegative Matrix Factorization: Algorithms and Applications. SIAM Gene Golub Summer School, Aussois France, June 18, 2019

Chunxuan Shao. et. al., (2017). Robust classification of single-cell transcriptome data by nonnegative matrix factorization. Bioinformatics

Paul Fogel (2013). Permuted NMF: A Simple Algorithm Intended to Minimize the Volume of the Score Matrix

Philip M. Kim. et. al., (2003). Subsystem Identification Through Dimensionality Reduction of Large-Scale Gene Expression Data. Genome Research

Lucie N. Hutchins. et. al., (2008). Position-dependent motif characterization using non-negative matrix factorization. Bioinformatics

Patrik O. Hoyer (2004). Non-negative Matrix Factorization with Sparseness Constraints. Journal of Machine Learning 5

N. Fujita et al., (2018) Biomarker discovery by integrated joint non-negative matrix factorization and pathway signature analyses, Scientific Report

Art B. Owen et. al., (2009). Bi-Cross-Validation of the SVD and the Nonnegative Matrix Factorization. The Annals of Applied Statistics

Examples

ls("package:nnTensor")