This paper presents the Optimally-Pruned Extreme Learning Machine (OP-ELM) toolbox. This novel, fast and accurate methodology is applied to several regression and classification problems. The results are compared with widely known Multilayer Perceptron (MLP) and Least-Squares Support Vector Machine (LS-SVM) methods. As the experiments (regression and classification) demonstrate, the OP-ELM meth...

This paper is concerned with kernel-based techniques for automated categorization of laryngeal colour image sequences obtained by video laryngostroboscopy. Features used to characterize a laryngeal image are given by the kernel principal components computed using the N -vector of the 3-D colour histogram. The least squares support vector machine (LS-SVM) is designed for categorizing an image se...

In this present paper it deals with the Gender Classification from ECG signal using Least Square Support Vector Machine (LS-SVM) and Support Vector Machine (SVM) Techniques. The different features extracted from ECG signal using Heart Rate Variability (HRV) analysis are the input to the LS-SVM and SVM classifier and at the output the classifier, classifies whether the patient corresponding to r...

Extreme Support Vector Machine (ESVM) is a nonlinear robust SVM algorithm based on regularized least squares optimization for binary-class classification. In this paper, a novel algorithm for regression tasks, Extreme Support Vector Regression (ESVR), is proposed based on ESVM. Moreover, kernel ESVR is suggested as well. Experiments show that, ESVR has a better generalization than some other tr...

a quantitative structure–activity relationship (qsar) study is suggested for the prediction of biological activity (pic 50 ) of 3, 4-dihydropyrido [3 ,2-d] pyrimidone derivatives as p38 inhibitors. modeling of the biological activities of compounds of interest as a function of molecular structures was established by means of principal component analysis (pca) and least square support vector mac...

Spirometry test is an inevitable, essential screening test in the case of respiratory and lung related diseases. This work focuses on predicting FEV1, which is the most significant and one of the deciding value in making the conclusion on respiratory related disorders by Least Squares Support Vector Machine (LS SVM) regression. This prediction of FEV1 values will enhance the spirometric method,...

A quantitative structure-activity relationship (QSAR) study was conducted for the prediction of inhibitory activity of 1-phenyl[2H]-tetrahydro-triazine-3-one analogues as inhibitors of 5-Lipoxygenase. The inhibitory activities of the 1-phenyl[2H]-tetrahydro-triazine-3-one analogues modeled as a function of molecular structures using chemometrics methods such as multiple linear regression (MLR) ...

Least squares twin support vector machine (LS-TSVM) aims at resolving a pair of smaller-sized quadratic programming problems (QPPs) instead of a single large one as in the conventional least squares support vector machine (LS-SVM), which makes the learning speed of LS-TSVM faster than that of LS-SVM. However, same penalties are given to the negative samples when constructing the hyper-plane for...

To investigate the detection of rice exterior quality, a machine vision system was developed. The main characteristics of rice appearance including area, perimeter, roughness and minimum enclosing rectangle were calculated by image analysis. Least Squares Support Vector Machines, Naive Bayes Classifier and Back Propagation Artificial Neural Network were applied to achieve classification of head...