in this study, a prediction model based on support vector machines (svm) improved by introducing a volume weighted penalty function to the model was introduced to increase the accuracy of forecasting short term trends on the stock market to develop the optimal trading strategy. along with vw-svm classifier, a hybrid feature selection method was used that consisted of f-score as the filter part ...

In 1996 an Introduction to Radial Basis Function Networks was published on the web 2 along with a package of Matlab functions 3. The emphasis was on the linear character of RBF networks and two techniques borrowed from statistics: forward selection and ridge regression. This document 4 is an update on developments between 1996 and 1999 and is associated with a second version of the Matlab packa...

A diagnostic method along the lines of forward search is proposed to simultaneously study the effect of individual observations and features on the inferences made in linear regression. The method operates by appending dummy variables to the data matrix and performing backward selection on the augmented matrix. It outputs sequences of feature–outlier combinations which can be evaluated by plots...

We present and examine a novel Contribution-Selection algorithm (CSA) for feature selection based on the Multi-perturbation Shapley Analysis. The algorithm combines both the filter and wrapper approaches in a multi-phasic manner to estimate features’ usefulness and select them accordingly, either using forward selection or backward elimination. Empirical comparison of several feature selection ...

We present and study the Contribution-Selection algorithm (CSA), a novel algorithm for feature selection. The algorithm is based on the Multiperturbation Shapley Analysis, a framework which relies on game theory to estimate usefulness. The algorithm iteratively estimates the usefulness of features and selects them accordingly, using either forward selection or backward elimination. Empirical co...

Air quality prediction is highly important in view of the health impacts caused by exposure to air pollutants in urban air. This work has presented a model based on support vector machine (SVM) technique to predict daily average carbon monoxide (CO) concentrations in the atmosphere of Tehran. Two types of SVM regression models, i.e. -SVM and -SVM techniques, were used to predict average daily C...