presents the use of support vector machine (SVM) algorithm for fault diagnosis through discrete wavelet features extracted from … vibration signals of good and faulty conditions of the components of centrifugal pump. The classification accuracies were … computed for different types of classifiers such as artificial neural network (ANN), support vector machine (SVM) and J48 …

Classification arises in a wide range of applications. A variety of statistical tools have been developed for learning … classification rules from data. Understanding of their relative merits and comparisons help users to choose a proper method in … practice. This paper focuses on theoretical comparison of model-based classification methods in statistics with algorithmic …

Neural Network models outperform the SVM models in terms of global good classification rates and of reduction of Error type I …. In fact, the good classification rates are respectively 90.2% (NNM) and 70.13% (SVM) for the in-sample set and the error … two different statistical methods of classification (artificial neural network and Support Vector Machine). We use a …

the ML algorithms for analyzing variation in results, to find the best classification model and to analyze the merits and …

In this paper, classification task is performed by FRSVM. It is variant of FSVM and MFSVM. Fuzzy rough set takes care …