计算机科学
感知器
人工智能
机器学习
人工神经网络
多层感知器
模糊推理系统
领域(数学)
支持向量机
分类器(UML)
计算智能
径向基函数
自适应神经模糊推理系统
数据挖掘
模糊逻辑
模式识别(心理学)
模糊控制系统
数学
纯数学
作者
Pretesh B. Patel,Tshilidzi Marwala
标识
DOI:10.1142/s0129065710002255
摘要
A classification system that accurately categorizes caller interaction within Interactive Voice Response systems is essential in determining caller behaviour. Field and call performance classifier for pay beneficiary application are developed. Genetic Algorithms, Multi-Layer Perceptron neural network, Radial Basis Function neural network, Fuzzy Inference Systems and Support Vector Machine computational intelligent techniques were considered in this research. Exceptional results were achieved. Classifiers with accuracy values greater than 90% were developed. The preferred models for field 'Say amount', 'Say confirmation' and call performance classification are the ensemble of classifiers. However, the Multi-Layer Perceptron classifiers performed the best in field 'Say account' and 'Select beneficiary' classification.
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