A Comparative Study On Different Meta-Cognitive Learning For Classification Problems

S Padma, A Arun Joseph

Abstract


Classification is an important concept of Data mining. Data mining deals with two types of learning which includes supervised learning and unsupervised learning. Neural networks are also included for classification. Different machine learning techniques are implied in classification for better accuracy and time efficiency. Meta-cognitive learning is a machine learning concept which involves the learning tactics as what-to-learn, when-to-learn and how-to-learn. This paper gives a comparative study of different meta-cognitive learning algorithms. Performance analysis of different datasets is analyzed and the results are compared.


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