In this paper, Support Vector Regression (SVR) training models using three different kernels: polynomial, Radial Basis Function (RBF), and mixed kernels, are constructed to demonstrate the training performance of unarranged data obtained from 32 virtual 3-D computer models. The 32 samples used as input data for training the three SVR models are represented by the coordination value sets of poin...

This paper describes the design of multi-category support vector machines (SVMs) for classification of bags. To train and test the SVMs a collection of 120 images of different types of bags were used (backpacks, small shoulder bags, plastic flexible bags, and small briefcases). Tests were conducted to establish the best polynomial and Gaussian RBF (radial basis function) kernels. As it is well ...

We conduct an empirical analysis to investigate the relationship between thirty seven different source code metrics with fifteen different Web Service QoS (Quality of Service) parameters. The source code metrics used in our experiments consists of nineteen Object-Oriented metrics, six Baski and Misra metrics, and twelve Harry M. Sneed metrics. We apply Principal Component Analysis (PCA) and Rou...

We study two fundamental problems related to finding subgraphs: (1) given graphs G and H, Subgraph Test asks if H is isomorphic to a subgraph of G, (2) given graphs G, H, and an integer t, Packing asks if G contains t vertex-disjoint subgraphs isomorphic to H. For every graph class F , let F-Subgraph Test and F-Packing be the special cases of the two problems where H is restricted to be in F . ...