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This paper proposes a novel method for constructing SVM ensembles for achieving improved image classification performance. The use of an SVM ensemble, instead of a single classifier, normally aims at reducing the training complexity and improving the performance. SVM ensembles are constructed by combining a set of base classifiers. While the traditional combination methods primarily consider an individual...
Ensemble learning is a method to improve the performance of classification and prediction algorithms. It has received considerable attention because of its prominent generalization and performance improvement. However, its performance can be degraded due to multicollinearity problem where multiple classifiers of an ensemble are highly correlated with. This paper proposes genetic algorithm-based coverage...
There are a lot of different methods in pattern classification, in which one of the most popular is the Support Vector Machine. Lots of tools have been developed to improve SVM classification, mainly the development of new classifying methods and the employment of SVM ensembles. Meanwhile, evolutionary algorithms are recognized tools to solve optimization problems, and have in the genetic algorithm...
A vehicle recognition algorithm is proposed to solve imbalanced datasets in vehicle recognition based on SVM ensembles. Moreover, an improved Wavelet feature algorithm is also presented. Experimental results show that the presented method has high precision and recall. Furthermore, the system performance can also be improved by increasing learning and has better application.
A motorcycle detection algorithm is proposed to solve imbalanced datasets in motorcycle recognition based on SVM ensembles. Moreover, an improved Wavelet feature algorithm is also presented. Experimental results show that the presented method has high precision and recall. Furthermore, the system performance can also be improved by increasing learning.
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