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...iversiteit Leuven, Department of Electrical Engineering, ESAT-SISTA Kardinaal Mercierlaan 94, B-3001 Leuven (Heverlee), Belgium, e-mail: johan ... Performance modeling of analog integrated circuits using ... ... [email protected] Abstract. In this letter we discuss a least squares version for support vector machine (SVM) classi- ﬁers. Due to equality ... Least-Squares Support Vector Machines, a modified version of standard Support Vector Machines, reformulates the learning algorithm into the least-squares framework. It goes from solving a quadratic problem to a set of linear equations. A well-known property with respect to such least-squares formulation ... Least-squares support-vector machine - Wikipedia ... . It goes from solving a quadratic problem to a set of linear equations. A well-known property with respect to such least-squares formulation is the lack of sparseness. Sparseness is related to the induced model be expressed in terms ... Least squares support vector machine classifiers Least squares support vector machines (LS-SVM) is an SVM version which involves equality instead of inequality constraints and works with a least squares cost function. In this way, the solution ... Second, the least squares support vector machines (LS-SVM) was applied to distinguish documents of different dating, and the accuracy was 99.26%. In order to find interested wavenumber that ... Least Squares Support Vector Machines are reformulation to the standard SVMs that lead to solving linear KKT systems. The algorithm is based on the minimization of a classical penalized least-squares cost function. The current implementation approximates the kernel matrix by an incomplete Cholesky factorization obtained by the In machine learning, support-vector machines (SVMs, also support-vector networks) are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis.The Support Vector Machine (SVM) algorithm is a popular machine learning tool that offers solutions for both classification and regression problems. Fuzzy Least Squares Twin Support Vector Machines Javad Salimi Sartakhtia,, Nasser Ghadiri a, Homayun Afrabandpey , Narges Yousefnezhadb aDepartment of Electrical and Computer Engineering, Isf...