An Improved Alias Classification using Logistic Regression with Particle Swarm Optimization
M. Subathra, Raju Nedunchezhian · Indian Journal of Science and Technology · 2015
An improvement in detection of alias names of an entity is an important factor in many cases like terrorist and criminal network. In this paper, the social network properties are used to construct a feature set for classification. The proposed particle swarm optimization is used to optimize the regularization parameter of the logistic regression and improve the accuracy of the entity alias classification significantly to 4.98% compared to that of the logistic regression. The experimental results demonstrated its performance and the results are compared to the logistic regression with alias detection dataset. Keywords: Alias Classification, Logistic Regression, Particle Swarm Optimization, Regularization