Diabetes Mellitus is a disease where the body cannot use insulin properly, so this one of health problems in various countries. can be fatal, cause other diseases, and even lead to death. Based on this, it essential have prediction activities find out disease. The SVM algorithm used classifying diseases. This study aimed compare accuracy, precision, recall, F1-Score values with kernels data pre...

Pattern classiication may be viewed as an ill-posed, inverse problem to which the method of regularization be applied. In doing so, a proper theoretical framework is provided for the application of radial basis function (RBF) networks to pattern classiication, with strong links to the classical kernel regression estimator (KRE)-based classiiers that estimate the underlying posterior class densi...

This paper is intender to be a simple example illustrating some of the capabilities of Radial basis function by pruning with QLP decomposition. The applicability of the radial basis function (RBF) type function of artificial neural networks (ANNS) approach for re-estimate the Box, Traingle, Epanechnikov and Normal densities. We propose an application of QLP decomposition model to reduce to the ...

PROBLEM SETTING Support vector machines (SVMs) are very popular tools for classification, regression and other problems. Due to the large choice of kernels they can be applied with, a large variety of data can be analysed using these tools. Machine learning thanks its popularity to the good performance of the resulting models. However, interpreting the models is far from obvious, especially whe...

The task of RBF kernel selection in Relevance Vector Machines (RVM) is considered. RVM exploits a probabilistic Bayesian learning framework offering number of advantages to state-of-the-art Support Vector Machines. In particular RVM effectively avoids determination of regularization coefficient C via evidence maximization. In the paper we show that RBF kernel selection in Bayesian framework req...

Script identification is one of the challenging steps in the development of optical character recognition system for bilingual or multilingual documents. In this paper an attempt is made for identification of English numerals at word level from Punjabi documents by using Gabor features. The support vector machine (SVM) classifier with five fold cross validation is used to classify the word imag...

Computational units induced by convolutional kernels together with biologically inspired perceptrons belong to the most widespread types of units used in neurocomputing. Radial convolutional kernels with varying widths form RBF (radial-basis-function) networks and these kernels with fixed widths are used in the SVM (support vector machine) algorithm. We investigate suitability of various convol...

In this paper, an evaluation using various training data sets for discrimination of dysmorphic facial features with distinctive information will be presented. We utilize Gabor Wavelet Transform (GWT) as feature extractor, K-Nearest Neighbor (K-NN) and Support Vector Machines (SVM) as statistical classifiers. We analyzed the classification accuracy according to increasing dimension of training d...

We consider distance-based similarity measures for real-valued vectors of interest in kernel-based machine learning algorithms. In particular, a truncated Euclidean similarity measure and a self-normalized similarity measure related to the Canberra distance. It is proved that they are positive semi-definite (p.s.d.), thus facilitating their use in kernel-based methods, like the Support Vector M...