A novel salp swarm clustering algorithm for prediction of the heart diseases

Heart <span>diseases have a severe impact on human life and health. Cardiovascular deaths diseases increased at fast rate worldwide. The early prediction of these is necessary to prevent deaths. Now day; considerable amount medical information available collected as databases. An efficient technique required analyse this data predict the disease. Clustering can help practitioners in diagnosis by classifying patient’s for techniques such based each patient-generated A new model salp swarm algorithm support vector machine proposed research predicting heart diseases. Salp used select useful features from database. Support classifier Results obtained are compared with other algorithms literature. It observed that approach produces better results accuracy 98.75% 98.46% dataset 1 2, respectively. In addition this, converges significantly less time comparison algorithms. This might become perfect supporting tool </span>practitioners.