Multi-Agent System Based on Data Mining Algorithms to Detect Breast Cancer

Abstract

Recently, data mining and intelligent agents have emerged as two domains with tremendous potential for research. The capacity of agents to learn from their experience complements the data mining process. This chapter aims to study a multi-agent system that evaluates the performance of three well-known data mining algorithms—artificial neural network (ANN), support vector machines (SVM), and logistic regression or logit model (LR)—based on breast cancer data (WBCD). Then the system aggregates the classifications of these algorithms with a controller agent to increase the accuracy of the classification using a majority vote. Extensive studies are performed to evaluate the performance of these algorithms using various differential performance metrics such as classification rate, sensitivity, and specificity using different software modules. In the end, the authors see that this system gives more autonomy and initiative in the medical diagnosis and the agent can dialogue to share their knowledge.