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首页> 外文会议>Machine Learning and Applications, 2009. ICMLA '09 >Genetic Algorithms, Neural Networks, Fuzzy Inference System, Support Vector Machines for Call Performance Classification
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Genetic Algorithms, Neural Networks, Fuzzy Inference System, Support Vector Machines for Call Performance Classification

机译：遗传算法，神经网络，模糊推理系统，用于呼叫性能分类的支持向量机

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摘要

Accurate classification of caller interactions within Interactive Voice Response systems would assist corporations to determine caller behavior within these telephony applications. This paper details the development of such a classification system for a pay beneficiary application. Fuzzy Inference Systems, Multi-Layer Perceptron, Support Vector Machine and ensemble of classifiers were developed. Accuracy, sensitivity and specificity performance metrics were computed as well as compared for these classification solutions. Ideally, a classifier should have high sensitivity and high specificity. Exceptional results were achieved. The ensemble of classifiers is the preferred solution, yielding an accuracy of 99.17%.
机译：交互式语音响应系统中呼叫者交互的准确分类将有助于公司确定这些电话应用程序中的呼叫者行为。本文详细介绍了这种针对薪酬受益人的分类系统的开发。开发了模糊推理系统，多层感知器，支持向量机和分类器集合。计算并比较了这些分类解决方案的准确性，敏感性和特异性性能指标。理想地，分类器应具有高灵敏度和高特异性。取得了优异的成绩。分类器集成是首选解决方案，其准确性为99.17％。

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