PatternRecog_GAM_SparityRegression is a MATLAB toolbox for extracting meaningful patterns affected by a certain disease from a large data which are biased to other factors, e.g., age, gender, socioeconomic status, and scanner type. To find the meaningful patterns being able to distinguish group differences while suppressing the impact of other factors, we jointly parameterize a general additive model for desensitizing the image scores and a sparsity-constrained, logistic-regression model for classification by maximizing a likelihood. The software was developed by the Center for Health Sciences group at SRI International at Menlo Park.
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License:PatternRecog_GAM_SparityRegression license
Domain:Computational Neuroscience

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gam_sparityreg: Joint GAM and Sparse-Constraint Logistic Regression (ver1) release posted by Sang Hyun Park on Nov 6