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Table 2 Principles to realize a fair integration of different data matrices.

From: A structured overview of simultaneous component based data integration

Principle

Methods aiming at this principle

Same weight for all matrices (naive approach)

SCA-P

More weight for smaller matrices

SUM-PCA, MFA

More weight for less redundant matrices

MFA

More weight for matrices with more stable predictive information

PCovR

More weight for matrices that share more information with other matrices (K > 2)

STATIS