Area Under the Curve (AUC) and Receiver Operating Characteristic (ROC) curves for supervised classification
Horizontal Partial Least Squares (PLS) integration
Horizontal Partial Least Squares - Discriminant Analysis (PLS-DA) integration
Horizontal sparse Partial Least Squares (sPLS) integration
Horizontal sparse Partial Least Squares - Discriminant Analysis (sPLS-DA) integration
Breast Cancer multi omics data from TCGA
Clustered Image Maps (CIMs) ("heat maps")
Clustered Image Maps (CIMs) ("heat maps") for DIABLO
16S microbiome data: most diverse bodysites from HMP
Estimate the parameters of regularization for Regularized CCA
Image Maps of Correlation Matrices between two Data Sets
Horizontal and Vertical Discriminant Analysis integration
Horizontal and Vertical sparse integration with variable selection
Horizontal and Vertical Discriminant Analysis integration with variable selection
Vertical integration with variable selection
Vertical Discriminant Analysis integration with variable selection
PLS-derived methods: one function to rule them all
Identification of zero- or near-zero variance predictors
Relevance Network for (r)CCA and (s)PLS regression
Non-linear Iterative Partial Least Squares (NIPALS) algorithm
Tune the number of principal components in PCA
Compute evaluation criteria for PLS, sPLS, PLS-DA, sPLS-DA, MINT and DIABLO
Graphical output for the DIABLO framework
Plot of Individuals (Experimental Units)
Partial Least Squares Discriminant Analysis (PLS-DA).
Predict Method for (mint).(block).(s)pls(da) methods
Print Methods for CCA, (s)PLS, PCA and Summary objects
Sparse Partial Least Squares Discriminant Analysis (sPLS-DA)
Small version of the small round blue cell tumors of childhood data
divides a data matrix in a list of matrices defined by a factor
Overall tuning function that can be used to tune several methods
Estimate the parameters of mint.splsda method
Tuning functions for multilevel analyses
Simulated data based on the vac18 study for multilevel analysis
Variable Importance in the Projection (VIP)
Within matrix decomposition for repeated measurements (cross-over design)
mixOmics wrapper for Regularised Generalised Canonical Correlation Analysis (rgcca)
mixOmics wrapper for Sparse Generalised Canonical Correlation Analysis (sgcca)