The twin support vector machine and its extensions have made great achievements in dealing with binary classification problems. However, it suffers from difficulties effective solution of multi-classification fast model selection. This work devotes to the regularization parameter tuning algorithm for multi-class machine. Specifically, a novel sample data set partition strategy is first adopted,...

in the last two decade the use of aerial laser scanner (als) or lidar (light detection and ranging) sensor in geomatics engineering and surveying application has augmented significantly . the main reason of the mentioned phenomenon is the reliability and accuracy of the data obtained by lidar sensors. the output of lidar is unclassified 3d point cloud. classification of the lidar point clouds i...

classification ensemble, which uses the weighed polling of outputs, is the art of combining a set of basic classifiers for generating high-performance, robust and more stable results. this study aims to improve the results of identifying the persian handwritten letters using error correcting output coding (ecoc) ensemble method. furthermore, the feature selection is used to reduce the costs of ...

a robust and reliable quantitative structure-property relationship (qspr) study was established to forecast the melting points (mps)  of a diverse and long set including 250 drug-like compounds. based on the calculated descriptors by dragon software package, to detect homogeneities and to split the whole dataset into training and test sets, a principal component analysis (pca) approach was used...

Predicting protein-protein interactions represent a key step in understanding proteins functions. This is due to the fact that proteins usually work in context of other proteins and rarely function alone. Machine learning techniques have been applied to predict protein-protein interactions. However, most of these techniques address this problem as a binary classification problem. Although it is...

How to extend standard support vector machines to solve multi-class classification problem and yield the outputs in the frame of Dempster-Shafer theory is useful. The multi-class probability support vector machine is proposed, firstly. The Dempster-Shafer theory based multi-class support vector machine is designed by constructing probability support vector machines for binary classification usi...

structural repetitive subsequences are most important portion of biological sequences, which play crucial roles on corresponding sequence’s fold and functionality. biggest class of the repetitive subsequences is “transposable elements” which has its own sub-classes upon contexts’ structures. many researches have been performed to criticality determine the structure and function of repetitive su...

Steinwart was the first to prove universal consistency of support vector machine classification. His proof analyzed the ‘standard’ support vector machine classifier, which is restricted to binary classification problems. In contrast, recent analysis has resulted in the common belief that several extensions of SVM classification to more than two classes are inconsistent. Countering this belief, ...