Add to ORKGAbstract. In this paper we describe a method for data set reduction by effective use of Multi-category Proximal Support Vector Machine (MPSVM). By using the Linear MPSVM Formulation in an iterative manner we identify the outliers in the data set and eliminate them. A k-Nearest Neighbor (k-NN) classifier is able to classify points using this reduced data set without significant loss of accuracy. We present experiments on a well known large OCR data set to validate our claims.
Abstract- We present a fast iterative algorithm for identifying the Support Vectors of a given set o...
Research on Smooth Support Vector Machine (SSVM) for classification problem is an active field in da...
As one of the most important state-of-the-art classification techniques, Support Vector Machine (SVM...
Abstract. We present a tutorial introduction to Support Vector Machines (SVM) and try to show using ...
<p>The Proximal Support Vector Machine Classifier: The planes around which points of the sets A+ an...
Part 7: Optimization-SVM (OPSVM)International audienceAlthough Support Vector Machines (SVMs) are co...
Proximal Support Vector machine based on Least Mean Square Algorithm classi-fiers (LMS-SVM) are tool...
Support vector machines (SVMs) have good accuracy and generalization properties, but they tend to be...
. The solution of binary classification problems using support vector machines (SVMs) is well develo...
In this paper, we present an algorithm that can classify large-scale text data with high classificat...
Support vector machine (SVM) is a recent method to classify the data. SVM has been proved as a power...
The neighborhood rough set (NRS) is used to remove redundant features after identifying neighborhood...
In this dissertation, we study the multi-category support vector machines (k-SVM). The design of the...
In this paper, we propose a support vector machines (SVMs) method of classifying image regions hiera...
AbstractIn this paper, we propose an efficient lp-norm (0<p<1) Proximal Support Vector Machine by co...
Abstract- We present a fast iterative algorithm for identifying the Support Vectors of a given set o...
Research on Smooth Support Vector Machine (SSVM) for classification problem is an active field in da...
As one of the most important state-of-the-art classification techniques, Support Vector Machine (SVM...
Abstract. We present a tutorial introduction to Support Vector Machines (SVM) and try to show using ...
<p>The Proximal Support Vector Machine Classifier: The planes around which points of the sets A+ an...
Part 7: Optimization-SVM (OPSVM)International audienceAlthough Support Vector Machines (SVMs) are co...
Proximal Support Vector machine based on Least Mean Square Algorithm classi-fiers (LMS-SVM) are tool...
Support vector machines (SVMs) have good accuracy and generalization properties, but they tend to be...
. The solution of binary classification problems using support vector machines (SVMs) is well develo...
In this paper, we present an algorithm that can classify large-scale text data with high classificat...
Support vector machine (SVM) is a recent method to classify the data. SVM has been proved as a power...
The neighborhood rough set (NRS) is used to remove redundant features after identifying neighborhood...
In this dissertation, we study the multi-category support vector machines (k-SVM). The design of the...
In this paper, we propose a support vector machines (SVMs) method of classifying image regions hiera...
AbstractIn this paper, we propose an efficient lp-norm (0<p<1) Proximal Support Vector Machine by co...
Abstract- We present a fast iterative algorithm for identifying the Support Vectors of a given set o...
Research on Smooth Support Vector Machine (SSVM) for classification problem is an active field in da...
As one of the most important state-of-the-art classification techniques, Support Vector Machine (SVM...