In this paper we present an integer programming formulation of the minimum sphere covering problem that seeks to construct a minimum number of spheres to represent the training data. Using soft threshold functions, we further derive a linear programming problem whose solution gives rise to radial basis function classifiers and sigmoid function classifiers. In contrast to traditional RBF and sig...

Problems faced in contemporary practice should be understood to improve requirements engineering processes. System requirements are descriptions of services provided by a system and operational constraints. NonFunctional Requirements (NFR) defines overall qualities/attributes of the system. NFR analysis is a significant activity in this branch of engineering. In this study, a methodology for cl...

BBM, or fuel oil, is one of the essential needs Indonesian people. The government's policy regarding increase in prices raises many opinions from public. Twitter social media that people often use to express on a topic. In this study, sentiment analysis was carried out public opinion price media. This research expected help determine with positive, neutral and negative sentiments. method used S...

With the aim of developing an accurate pathological brain detection system, we proposed a novel automatic computer-aided diagnosis (CAD) to detect pathological brains from normal brains obtained by magnetic resonance imaging (MRI) scanning. The problem still remained a challenge for technicians and clinicians, since MR imaging generated an exceptionally large information dataset. A new two-step...

Discriminative methods such as SVM, have been validated extremely efficient in pattern recognition issues. We present a systematic study on smile detection with different SVM classifiers. We experimented with linear SVM classifier, RBF kernel SVM classifier and a recentlyproposed local linear SVM (LL-SVM) classifier. In this paper, we focus on smile detection in face images captured in real-wor...

Meshfree methods have been formulated based on Galerkin type weak formulation and collocation type strong formulation. The approximation functions commonly used in the Galerkin based meshfree methods are the moving least-squares (MLS) and reproducing kernel (RK) approximations, while the radial basis functions (RBFs) are usually employed in the strong form collocation method. Galerkin type form...

In this abstract paper, we introduce a new kernel learning method by a nonparametric density estimator. The estimator consists of a group of k-centroids clusterings. Each clustering randomly selects data points with randomly selected features as its centroids, and learns a one-hot encoder by one-nearest-neighbor optimization. The estimator generates a sparse representation for each data point. ...

Feature extraction is among the most important problems in face recognition sys-tems. In this paper, we propose an enhanced kernel discriminant analysis (KDA)algorithm called kernel fractional-step discriminant analysis (KFDA) for nonlinearfeature extraction and dimensionality reduction. Not only can this new algorithm,like other kernel methods, deal with nonlinearity requir...

Credit scoring models are very important tools for financial institutions to make credit granting decisions. In the last few decades, many quantitative methods have been used for the development of credit scoring models with focus on maximizing classification accuracy. This paper proposes the credit scoring models with the area under receiver operating characteristics curve (AUC) maximization b...

OBJECTIVES Diabetes is increasing in worldwide prevalence, toward epidemic levels. Diabetic neuropathy, one of the most common complications of diabetes mellitus, is a serious condition that can lead to amputation. This study used a multicategory support vector machine (MSVM) to predict diabetic peripheral neuropathy severity classified into four categories using patients' demographic character...