2019 · 71 citations · 6 references
ComputingComputer ScienceData ScienceData MiningMachine LearningStatistical LearningClassificationEnsemble LearningEnsemble MethodsKernel MethodsPattern RecognitionSupport Vector MachinesAdaboostClassification AccuracyClassification AlgorithmsClassifier FusionMachine Learning ClassificationSupport Vector ClassificationSupport Vector Machine ClassificationSvms
In this paper, we use AdaBoost algorithm as a framework to design a new classification algorithm. The algorithm combines the characteristics of SVM and AdaBoost algorithms. The SVM algorithm is used as a weak classifier algorithm. AdaBoost is used to cascade multiple weak classifiers to form a strong classifier, thus achieving more accurate classification. In the experiment, this paper uses SVM algorithm, AdaBoost algorithm and the algorithm of this paper to carry out several comparison experiments. The experimental results show that the algorithm can achieve higher accuracy classification in data sets of various sizes. At the same time, the algorithm is moderate in calculation speed, so the new algorithm proposed in this paper is better than the traditional SVM or AdaBoost classification algorithm.
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Pattern Classifier Design by Linear Programming
Fred W. Smith · IEEE Transactions on Computers · 1968 · 147 citations