Sentence examples for based classifiers were developed from inspiring English sources

LR as well as multilayer perceptron neural network (MLPNN) based classifiers were developed and compared in relation to their accuracy in classification of EEG signals.

Logistic regression as well as multilayer perceptron neural network (MLPNN) based classifiers were developed and compared in relation to their accuracy in classification of EEG signals.

Logistic regression as well as feedforward error backpropagation artificial neural networks (FEBANN) and wavelet neural networks (WNN) based classifiers were developed and compared in relation to their accuracy in classification of EEG signals.

Linear and nonlinear logistic regression as well as feedforward error backpropagation artificial neural networks (FEBANN) and probabilistic neural networks (PNN) based classifiers were developed and compared in relation to their accuracy in classification of bacterial growth/no growth data pertaining to pathogenic Escherichia coli R31 as affected by temperature and water activity.

Using the first derivatives or the rank ordered first derivatives of the spectral regions, pair-wise Linear Discriminant Analysis based classifiers were developed.

Since many gene expression based classifiers are developed retrospectively, there is often little control of the sample size.

Based on cross-correlation analysis, 24 support vector machine (SVM) classifiers were developed for the multi-SVM model.

The diagnostic classifiers were developed in 'R' v. 2.7.

Three new 14-3-3 14-3-3 14-3-3ere developed in this work.

Classifiers were developed with the training set, and the reliability of these classifiers was examined with the test set.

Backpropagation neural-network (BPNN) based binary classifiers are developed for authentication utilizing the features extracted.