The main aim of the present study is the comparative evaluation of SVM and MLDA in extracting voxels relevant to the discrimination of activation patterns.

May 15, 2009 · The aim of the current study is the evaluation of SVM and Maximum uncertainty Linear Discrimination Analysis (MLDA) in extracting the voxels ...

The aim of the current study is the evaluation of SVM and Maximum uncertainty Linear Discrimination Analysis (MLDA) in extracting the voxels containing ...

The aim of the current study is the evaluation of SVM and Maximum uncertainty Linear Discrimination Analysis (MLDA) in extracting the voxels containing ...

Evaluating SVM and MLDA in the extraction of discriminant regions for mental state prediction (vol 46, pg 105, 2009). Joao Ricardo Sato, Andre Fuita, Carlos ...

Evaluating SVM and MLDA in the extraction of discriminant regions for mental state prediction. Sato, J.R.; Fujita, A. Thomaz, C.E.; Martin, M.d.G.M.; Mourão ...

Sep 9, 2024 · These algorithms mainly aim to select a minimum set of voxels necessary for constructing a classifier with the best predictive accuracy [19]. ..

Evaluating SVM and MLDA in the extraction of discriminant regions for mental state prediction. Authors: Sato JR, Fujita A, Thomaz CE, Martin Mda G, Mourao ...

Evaluating SVM and MLDA in the extraction of discriminant regions for mental state prediction ; dc.contributor.author, Sato J. R. ; dc.contributor.author, FUJITA, ...

Read online or download for free from Z-Library the Book: Evaluating SVM and MLDA in the extraction of discriminant regions for mental state prediction, ...