• Naga Subrahmanyeswari.N.
• G.Satya Suneetha

Machine learning is the field of study where the computers gain the ability to learn without being programmed and this learning happens from the models they build earlier. Classification is a common task in data mining and its applications which is one of the supervised learning techniques. With classification, the data sets are predicted to belong to any one of the set of predefined class labels. Once the classification models are built, they need to be evaluated on the basis of any performance criteria available. Evaluation of the classifiers is an important task for selecting the best model built. This paper presents an overview on the available metrics for evaluating the classifiers.

Machine learning, Classification, Evaluation

"Classification Evaluation metrics in Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 10, page no.c684-c687, October-2022, Available :http://www.jetir.org/papers/JETIR2210288.pdf

"Classification Evaluation metrics in Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 10, page no. ppc684-c687, October-2022, Available at : http://www.jetir.org/papers/JETIR2210288.pdf