Genetic Algorithms, Neural Networks, Fuzzy Inference System, Support Vector Machines for Call Performance Classification

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%.