MVPAModels | R Documentation |
An environment containing custom classification models for MVPA analysis.
MVPAModels
An environment with the following models:
Correlation-based classifier using template matching with options (pearson, spearman, kendall)
Alias for corclass
Shrinkage Discriminant Analysis (SDA) without parameter tuning
SDA with bootstrap resampling and feature selection
Elastic net classifier (glmnet) with optimized alpha/lambda via EPSGO
SDA with sparsity constraints and feature selection
SDA with feature ranking and selection via higher criticism
Multi-Group Sparse Discriminant Analysis
Modified LDA classifier for high-dimensional data
High-Dimensional Regularized Discriminant Analysis
Models are accessed via load_model(name)
. Each model specification includes fit
, predict
, and prob
methods.
# Load simple SDA classifier
model <- load_model("sda_notune")
# Load correlation classifier
model <- load_model("corclass")
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