An advanced manta ray search optimisation with likelihood marginal classification mechanism for ECG arrhythmia detection

The proposed work objects to develop an advanced optimisation-based classification system for identifying the arrhythmia disease with increased accuracy and reduced error rate. The optimal features are selected using the manta ray search optimisation (MRSO) technique. The likelihood marginal classification (LMC) approach is employed to predict the classified label as whether normal or disease affected. During analysis, the different types of performance measures are used to evaluate the results of the proposed approach. Also, the obtained values are compared with the existing techniques for showing the effectiveness of the proposed model.