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3 projects in result set.
MPAgenomics  This package contains an implementation of the lars algorithm for the lasso and fusion penalization. It works even if the number of covariate is greater than the number of individuals.  
Tags: lasso, lars, sparse linear model, C++, genomic, Bioinformatics, Multivariate Analysis, Multivariate Regression, high dimentional data, low sample size high dimensional data, penalized regression  

Activity Percentile: 80 Activity Ranking: 9 Registered: 20130418 16:20 
concurrence topology  Concurrence topology is a method for analyzing the dependence structure in multivariate binary data. It is particularly well suited for describing highorder dependence.  
Tags: Multivariate Analysis, categorical, fMRI, high dimentional data, low sample size high dimensional data, multivariate, multivariate statistics, nonparametrics, nonparametric, time series  
This project has not yet categorized itself in the Trove Software Map  Activity Percentile: 0 Activity Ranking: 0 Registered: 20130220 19:07 
penalizedSVM  Feature selection for SVM classification in high dimensions using penalty functions L1, SCAD, Elastic Net (L1+L2) and Elastic SCAD (SCAD+L2) SVM. Choice of datadependent tuning parameters: beside the standard fixed grid an interval search is implemented  
Tags: Classification, feature selection, machine learning, tuning parameters, penalty functions, high dimentional data, low sample size high dimensional data, Bioinformatics, Machine Learning  
This project has not yet categorized itself in the Trove Software Map  Activity Percentile: 0 Activity Ranking: 0 Registered: 20120619 15:40 