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International Journal of Bio-Science and Bio-Technology Vol.6, No.2 (2014), pp.69-82 ISSN: 2233-7849 IJBSBT Copyright 2014 SERSC Feature Selection based Least Square Twin Support Vector Machine for Diagnosis of Heart Disease Divya Tomar and Sonali Agarwal Indian Institute of Information and Technology, Allahabad, India [email protected] and [email protected] Abstract It is evident from various researches that disease diagnosis using machine learning methods has been increasing rapidly. In this research work, feature selection based Least Square Twin Support Vector Machine (LSTSVM), which is a machine learning method, is used for diagnosis of heart diseases. In this approach F-score is used to calculate the weight of each feature and then features are selected according to their weight. The higher weight is assigned to the feature having high F-score. Grid search approach is also utilized to select the best value of classifier's parameters in order to enhance its performance. The heart- statlog disease dataset is used in this study, which is taken from the UCI repository. The performance of proposed model with different feature sets has been evaluated for different training-test datasets. The results indicate that LSTSVM model with 11 features has achieved highest accuracy. The results are very promising as compared to the other approaches proposed earlier. Keywords: Heart Disease, F-Score, LSTSVM 1. Introduction Cardiovascular Disease (CVD) is one of the important and crucial heart diseases which occur among both men and women and is also the leading cause of the deaths in the world. CVD may occur in several forms, for example abnormal blood pressure, valvular heart disease, cerebrovascular, coronary artery disease and heart failures. CVD affects the heart as well as its surrounding blood vessels and it can be caused due to abnormalities in the heart muscles. Fibrous elements and inflammatory cells increase the hardness and narrowness of the blood vessels. Fatty deposits are also harmful and responsible for CVD [1]. So, it is important to identify the root causes responsible for the heart diseases. So their remedy could also be planned by using suitable methods. Figure 1 represents the pie chart of various diseases released by World Health Organization in 2008. It was estimated that 30% of all global death occur due to heart problems. Figure 2 shows the number of deaths in thousands due to different diseases in United States (US). It is clearly visible that the heart diseases are the leading cause of the deaths in US.
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International Journal of Bio-Science and Bio-Technology Vol.6, No.2 (2014) 70 Copyright 2014 SERSC Figure 1. Status of Cardiovascular disease-2008 ( World Health Organization ) [1] Figure 2. Number of deaths and ten leading causes recorded in United States, 2010 [2] In India, heart disease is observed as prime death cause in both rural and urban areas.
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