accelerometer data collected from three cities in Japan. The classifiers used were support vector machines (SVM), adaptive boosting …

Support Vector Machine (SVM) and a logistic regression (Logit). Among different financial ratios suggested as predictors of … accuracy the SVM has a lower model risk than the Logit on average and displays a more robust performance. This result holds …

presents the use of support vector machine (SVM) algorithm for fault diagnosis through discrete wavelet features extracted from … computed for different types of classifiers such as artificial neural network (ANN), support vector machine (SVM) and J48 …

taking the advantage of both SVM and BP networks and avoiding their defects. An actual instance addressed in the paper shows …

We propose a support vector machine (SVM)-based structural model to forecast the collapse of banking institutions in … procedure. We train an SVM model to classify banks as solvent and insolvent. The resulting model exhibits significant ability in …

Vector Machines (SVM) for financial data. The financial series are fitted into a family of Asymmetric Power ARCH (APARCH … inefficient when the data distribution shows departure from normality, so the current paper utilizes the nonparametric-based SVM … method and shows that it is more efficient than the QML under the skewed Student’s t-distributed error. As the SVM is a …