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The procedure for feature extraction in our proposed methods is as follows: (a) Frame blocking and pre-emphasis.
In the following sections we discuss the data we collected and employed, the procedure for feature extraction and selection, the implementation of the learning framework, and the evaluation of our system.
This results in a statistically sound procedure for feature selection, akin to forward stage-wise linear regression and the Lasso [ 27, 31], and a very efficient computational procedure.
Specifically, we performed 100 times 10-fold cross-validation for model validation, using a nested 10-fold cross-validation procedure for feature and model selection.
In the LPO approach, multiple (n = 5,000) training sets are obtained by stratified bootstrap resampling, and each training set is used as input to the inner-loop procedure for feature selection and training the classifier with the selected features.
In the Tclass system, Fisher's linear discriminant analysis and a step-wise optimization procedure for feature selection are used to analyze a batch adjusted data set [ 1] in two ways.
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This procedure first does all the process for feature detection and matching and iterates itself to search for the points found in the previous frame.
The ranked 340-feature list was then used in the IFS procedure for optimal feature selection and analysis.
The post printing processing procedure for 13K feature barcode arrays on GAPS™II slides was carried out as described above, with the exception that slides were first immersed and washed in 1% (w/v) BSA (fraction V), 0.1% SDS, 3× SSC for 2 minutes with mild agitation.
LARS is a computationally efficient procedure for multivariate feature selection, closely related to Lasso regression [ 27].
At the end of DWT method and statistical procedures used for feature extraction, five-dimensional feature vectors belonging to EEG segments related to every emotional state were obtained.
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CEO of Professional Science Editing for Scientists @ prosciediting.com