Ashutosh Kumar Dubey1,*, Umesh Gupta2, Sonal Jain2
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4523-4543, 2022, DOI:10.32604/cmc.2022.021148
- 11 October 2021
Abstract This study aims to empirically analyze teaching-learning-based optimization (TLBO) and machine learning algorithms using k-means and fuzzy c-means (FCM) algorithms for their individual performance evaluation in terms of clustering and classification. In the first phase, the clustering (k-means and FCM) algorithms were employed independently and the clustering accuracy was evaluated using different computational measures. During the second phase, the non-clustered data obtained from the first phase were preprocessed with TLBO. TLBO was performed using k-means (TLBO-KM) and FCM (TLBO-FCM) (TLBO-KM/FCM) algorithms. The objective function was determined by considering both minimization and maximization criteria. Non-clustered data… More >
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