In this paper, an Information Gain based Weighted Linear Vector Quantization (IG-WLVQ) is applied to heart dataset available in UCI machine learning repository for prediction of heart disease. It considers all attributes of the data set. The IG-WLVQ method weights the attributes according to their information gain while training the dataset. It is found that the classification accuracy approaches to 98.9%.
Keywords: LVQ, IG-WLVQ, ML