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The condensed nearest neighbor algorithm(CNN) is susceptible to pattern read sequence, abnormal patterns and so on. To deal with the above problems, through the analysis of the relationship between the whole dataset and the individual patterns, a new prototype selection algorithm is proposed based on the extended near neighbor relationship and the affinity changes. First, the proposed algorithm can...
Prototype selection aims at reducing the scale of datasets to improve prediction accuracy and operation efficiency by removing noisy or redundant patterns via the nearest neighbor classification algorithms. Genetic algorithms have been used recently for prototype selection and showed good performance, however, they have some drawbacks such as the deteriorated running effect, slow convergence for the...
Aiming at the weaknesses of PS-classifier, it is easily trapped into locally optimal solution and slow convergence velocity when it deals with the complex problems, an improved quantum-behaved particle swarm classifier has been proposed in the paper. Firstly, It introduce the weighted mean best position to improve the performance of QPSO (quantum-behaved particle swarm), and use a novel Michigan rule...
Teaching evaluation is a difficult task because of the difficulty of transforming teaching behavior into a quantitative problem. In this paper, an improved classification algorithm is proposed into the field of teaching evaluation by contrast with the traditional methods. Firstly, the key concepts of algorithms using in teaching evaluation are introduced, including the actual process of mining knowledge...
Essence of software testing is to choose a representative value (known as test case) from the input to perform the programs under test. The actual results of the programs will be checked to verify the consistency with the expected ones. If the results are different, it should take some correction and adjustment correspondingly. The existing method for test suite generation is mainly based on the test...
Applying image processing technologies to pedestrian detection has been a hot research topic in intelligent transportation systems (ITS). However, the existing video-based algorithms to extract background image may suffer their inefficiency in detecting slow or static pedestrians. To fill the gap, an improved Gaussian mixture model (GMM) for pedestrian detection is proposed in this paper. Three novel...
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