Abstract
The artificial neural network (ANN) is an important machine learning tool used in medical data classification for disease diagnosis. The learning algorithm in ANN training plays a crucial role in classification performance. In this paper, a recently developed swarm intelligence algorithm named as marine predators algorithm (MPA) is applied as a learning algorithm to train the ANN for classification tasks. The classification tasks are carried out on 10 well-known medical datasets. A comparative study is conducted with the classical Levenberg–Marquardt (LM) and particle swarm optimizer (PSO) algorithms. The classification results are analysed using multi-criteria decision-making (MCDM) method. The results with analysis establish that MPA outperforms other algorithms.
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