GitHub - mhollmann/easyupMVPA: A matlab toolbox for easily accessible multivariate analysis of (neuro-) scientific data.

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A matlab toolbox for easily accessible multivariate analysis of (neuro-) scientific data.

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Name		Name	Last commit message	Last commit date
Latest commit History 6 Commits
doc		doc
util		util
.gitignore		.gitignore
LICENSE.txt		LICENSE.txt
README.txt		README.txt
averageFeaturesInROIs.m		averageFeaturesInROIs.m
averageOverChunks.m		averageOverChunks.m
checkDataset.m		checkDataset.m
concatDatasets.m		concatDatasets.m
doHighpassFiltering.m		doHighpassFiltering.m
doLeaveOneOutCrossValidation_SVM.m		doLeaveOneOutCrossValidation_SVM.m
doLinearDetrending.m		doLinearDetrending.m
doRecursiveFeatureElemination_SVM.m		doRecursiveFeatureElemination_SVM.m
doRecursiveFeatureElemination_SVM_nestedLOOCV.m		doRecursiveFeatureElemination_SVM_nestedLOOCV.m
doRecursiveFeatureElemination_bootStrap_SVM.m		doRecursiveFeatureElemination_bootStrap_SVM.m
doRecursiveFeatureElemination_bootstrapping_SVM.m		doRecursiveFeatureElemination_bootstrapping_SVM.m
doSearchlightLOOCV_SVM.m		doSearchlightLOOCV_SVM.m
doSearchlightLeaveOneOutCrossValidation_SVM.m		doSearchlightLeaveOneOutCrossValidation_SVM.m
doZScoring.m		doZScoring.m
easyupMVPA_getGlobals.m		easyupMVPA_getGlobals.m
easyupMVPA_init.m		easyupMVPA_init.m
easyupMVPA_setGlobals.m		easyupMVPA_setGlobals.m
easyupMVPA_version.m		easyupMVPA_version.m
getDataSplitter.m		getDataSplitter.m
getEmpty2DDataset.m		getEmpty2DDataset.m
getEmpty4DDataset.m		getEmpty4DDataset.m
getROIAnalysisResult_ByRoiImageFile.m		getROIAnalysisResult_ByRoiImageFile.m
getSearchlightAdjacencyMatrix.m		getSearchlightAdjacencyMatrix.m
getSearchlightMatrix.m		getSearchlightMatrix.m
permuteClassIDs.m		permuteClassIDs.m
predict_RVM.m		predict_RVM.m
predict_SVM.m		predict_SVM.m
printDataSplitter.m		printDataSplitter.m
printDatasetInfo.m		printDatasetInfo.m
printResultStruct.m		printResultStruct.m
saveMatrix3DasNiftiInDatasetSpace.m		saveMatrix3DasNiftiInDatasetSpace.m
selectFeaturesBySelectionMap.m		selectFeaturesBySelectionMap.m
selectSamples.m		selectSamples.m
setDataset_chunks_ByAttribFile.m		setDataset_chunks_ByAttribFile.m
setDataset_chunks_ByVector.m		setDataset_chunks_ByVector.m
setDataset_classIDs_ByAttribFile.m		setDataset_classIDs_ByAttribFile.m
setDataset_classIDs_ByVector.m		setDataset_classIDs_ByVector.m
setDataset_data_ByFilelist.m		setDataset_data_ByFilelist.m
setDataset_data_ByMatrix.m		setDataset_data_ByMatrix.m
setDataset_featureSelectionMap_ByMatrix.m		setDataset_featureSelectionMap_ByMatrix.m
setDataset_mask_ByImageFile.m		setDataset_mask_ByImageFile.m
setDataset_mask_ByMatrix.m		setDataset_mask_ByMatrix.m
showDataAsImage.m		showDataAsImage.m
splitDataset.m		splitDataset.m
train_RVM.m		train_RVM.m
train_SVM.m		train_SVM.m

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easyupMVPA v 1.1

This toolbox is created to ease the multivariate analysis of (neuro) scientific data.
It is supporting Support Vector Machine (SVM) and Relevance Vector Machine (RVM) classification and regression.

License: GNU public license (see LICENSE)
Copyright (c) 2012, M.Hollmann, MPI Cognitive and Human Brain Sciences, Leipzig. All rights reserved.


Important:
This software is using the following implementations:

  libSVM v3.12      - Copyright (c) 2000-2012 Chih-Chung Chang and Chih-Jen Lin
  SparseBayes 2.0   - GNU General Public License, Copyright (c) 2009, M.Tipping
  niftiTools        - Copyright (c) 2009, Jimmy Shen