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A comparison of Extreme Learning Machine and Support Vector Machine classifiers

机译:极限学习机和支持向量机分类器的比较

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The comparison of two classifiers, the Extreme Learning Machine (ELM) and the Support Vector Machine (SVM) is considered for performance, resources used (neurons or support vector kernels) and computational complexity (speed). Both implementations are of similar type (C++ compiled as Octave .mex files) to have a better evaluation of speed and computational complexity. Our results indicate that ELM has similar performance to SVM in terms of speed while having the advantage of a smaller number of resources used.
机译:考虑了两个分类器,即极限学习机(ELM)和支持向量机(SVM)的性能,所用资源(神经元或支持向量核)和计算复杂度(速度)的比较。两种实现都是相似的类型(C ++编译为Octave .mex文件),以更好地评估速度和计算复杂性。我们的结果表明,ELM在速度方面具有与SVM相似的性能,同时具有使用较少资源的优势。

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