R/cvma: Cross-validation-based maximal associations

Assignment for Fall 2017 CS289: Machine Learning

Implementation of Fast ml-CCA from the ICCV-2015 work "Multi-Label Cross-Modal Retrieval"

Efficient sparse matrix implementation for various "Principal Component Analysis"

Cross-validation-based maximal associations

Time-dependent Canonical Correlation Analysis

MoMA: Modern Multivariate Analysis in R

Generalized Canonical Correlation Analysis - python 3 version

Deep Multiset Canonical Correlation Analysis - An extension of CCA to multiple datasets

Unsupervised Learning

This project implements canonical correlation analysis between two data matrices. I first create the latent dimensions between the two data matrices. Then I use Kmeans and hierarchical clustering on principal component to group individuals using the latent dimensions and the distance created by the canonical analysis. Last step, I give a profili…

This repository contains materials associated to the course "Multivariate Analysis" taught at the Faculty of Mathematics and Statistics (FME), UPC under the MESIO-UPC-UB Interuniversity Program under the instructors "Ferran Revertar", "Miguel Salicru" and "Jan Graffelman"

ISC method for M/EEG data

Sparse Canonical Correlation Analysis

Case Study in ranking U.S. cities based on a single linear combination of rating variables. Dimensionality techniques used in the analysis are Principal Component Analysis (PCA), Factor Analysis (FA), Canonical Correlation Analysis (CCA)

NeurIPS 2019: Deep RGB-D Canonical Correlation Analysis For Sparse Depth Completion

Canonical Analysis using R Notebook

❗ RGCCA — Regularized and Sparse Generalized Canonical Correlation Analysis for Multiblock Data