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M2SMJF (version 1.0)

Multi-Modal Similarity Matrix Joint Factorization

Description

A new method to implement clustering from multiple modality data of certain samples, the function M2SMjF() jointly factorizes multiple similarity matrices into a shared sub-matrix and several modality private sub-matrices, which is further used for clustering. Along with this method, we also provide function to calculate the similarity matrix and function to evaluate the best cluster number from the original data.

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Version

Install

install.packages('M2SMJF')

Monthly Downloads

146

Version

1.0

License

GPL (>= 2)

Maintainer

Xiaoyao Yin

Last Published

November 23rd, 2020

Functions in M2SMJF (1.0)

Standard_Normalization

Normalize the input matrix by column
affinityMatrix

To calculate the similarity matrix
M2SMJF

the main part for M2SMJF and clustering result
initialization

initialize the sub-matrix Ci into alpha*Li by SVD
cost

Calculate the cost
dist2chi

Calculate the chi-squared distance
Cal_NMI

calculate the normalized mutual information.
initialize_WL

Initialize from the similairty matrix list
simu_data_gen

Generate simulated data
new_modularity

Calculate the modularity
update_L

the function to update Li, for i=1,2,...,N
update_alpha

the function to update alpha
dist2bin

Calculate the agreement-based measurement
dist2eu

Calculate the Euclidean distance