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The accurate identification of the helicopter flight action is the basis for guiding the training of the pilot. According to the accuracy of the helicopter flight action recognition, the paper proposed a new decision-tree-based support vector machine method to realize the helicopter multi-flight action identification. Use the tree structure of the decision tree to solve the multi-class problem of...
Support Vector Machines (SVM), one of the new techniques for text classification, have been widely used in many application areas. SVM try to find an optimal hyperplane within the input space so as to correctly classify the binary classification problem. We present a novel heuristic text classification approach based on genetic algorithm (GA) and SVM. Simulation results demonstrate that GA and SVM...
In this paper, we present a SVM multi-classification decision-tree optimization algorithm based on genetic algorithm (GA) in order to overcome the defect of the error accumulation which is caused by the fixed tree configuration of traditional support vector machine (SVM) multi-classification decision-tree algorithms and the random positions of their decision nodes. We adopt the “classification margin”...
Suppose that we are interested in classifying n points in a z-dimensional space into two groups having response 1 and response 0 as the target variable. In some real data cases in customer classification, it is difficult to discriminate the favorable customers showing response 1 from others because many response 1 points and 0 points are closely located. In such a case, to find the denser regions...
In this paper, a novel classification approach is presented. This approach uses fuzzy if-then rules for classification task and employs a hybrid optimization method to improve the accuracy and comprehensibility of obtained outcome. The mentioned optimization method has been formulated by simulated annealing and genetic algorithm. In fact, the genetic operators have been used as perturb functions at...
Decision tree support vector machine (DTSVM), which combines SVM and decision tree using the concept of dichotomy, is proposed to solve the multi-class fault diagnosis tasks. Since the classification performance of DTSVM is closely related to its structure, genetic algorithm is introduced into the formation of decision tree, to cluster the multi-classes with maximum distance between the clustering...
An inverse problem of support vector machines (SVMs) was investigated. The inverse problem is how to split a given dataset into two clusters such that the margin between the two clusters attains the maximum. Here the margin is defined according to the separating hyper plane generated by support vectors. It is difficult to give an exact solution to this problem. An immunogenetic particle swarm incorporated...
Support vector machine (SVM) is novel type learning machine, based on statistical learning theory, which tasks involving classification, regression or novelty detection. This paper investigates an inverse problem of support vector machines (SVMs). The inverse problem is how to split a given dataset into two clusters such that the margin between the two clusters attains the maximum. Here the margin...
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