Pre-defined MVPA Classification Models

An environment containing custom classification models for MVPA analysis.

Usage

MVPAModels

Format

An environment with the following models:

corclass

Correlation-based classifier using template matching with options (pearson, spearman, kendall)

corsim

Alias for corclass

sda_notune

Shrinkage Discriminant Analysis (SDA) without parameter tuning

sda_boot

SDA with bootstrap resampling and feature selection

glmnet_opt

Elastic net classifier (glmnet) with optimized alpha/lambda via EPSGO

sparse_sda

SDA with sparsity constraints and feature selection

sda_ranking

SDA with feature ranking and selection via higher criticism

mgsda

Multi-Group Sparse Discriminant Analysis

lda_thomaz

Modified LDA classifier for high-dimensional data

hdrda

High-Dimensional Regularized Discriminant Analysis

Details

Models are accessed via load_model(name). Each implements caret's fit, predict, and prob methods.

Examples

# Load simple SDA classifier
model <- load_model("sda_notune")

# Load correlation classifier
model <- load_model("corclass")