支持向量机算法在移动计算平台上的复杂度评估

2017 5th International Symposium on Electrical and Electronics Engineering (ISEEE) Pub Date : 2017-10-01 DOI:10.1109/ISEEE.2017.8170701

Daniel Armanda, Alin-Gabriel Cococi, R. Dogaru

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引用次数: 0

摘要

支持向量机(SVM)是一种最先进的分类器模型，在计算移动平台上实现，并在同一平台上与SFSVC(超快速向量支持分类器)等低复杂度分类器进行性能评估。为了更好地进行比较，我们考虑了两种体系结构的类似实现，例如使用相同的基本线性代数库。获得了类似的性能，但提到SFSVC算法具有更紧凑的结构。

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Complexity evaluation of implementing the Support Vector Machine algorithm on mobile computing platforms

SVM (Support Vector Machine), a state of the art classifier model is implemented on a computational mobile platform and its performances are evaluated against a low complexity classifier such as SFSVC (Super Fast Vector Support Classifier) on the same platform. For a better comparison, similar implementation for the two architectures are considered, such as using the same basic linear algebra library. Similar performances are obtained, but with the mention that the SFSVC algorithm has a more compact structure.

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来源期刊

2017 5th International Symposium on Electrical and Electronics Engineering (ISEEE)

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