Application of Evolutionary Data Mining Algorithms to Insurance Fraud Prediction
In this paper the authors propose two kinds of Evolutionary Data Mining (EvoDM) algorithms to the insurance fraud prediction. One is GA-Kmeans by combining K-means algorithm with Genetic Algorithm (GA). The other is MPSO-Kmeans by combining K-means algorithm with Momentum-type Particle Swarm Optimization (MPSO). The dataset used in this study is composed of 6 attributes with 5000 instances for car insurance claim. These 5000 instances are divided into 4000 training data and 1000 test data.