Abstract Machine learning models have been widely used in numerous classification
problems and performance measures play a critical role in machine learning model …

The evaluation of classifiers' performances plays a critical role in construction and selection
of classification model. Although many performance metrics have been proposed in …

Performance metrics in classification are fundamental in assessing the quality of learning
methods and learned models. However, many different measures have been defined in the …

Several performance metrics are currently available to evaluate the performance of Machine
Learning (ML) models in classification problems. ML models are usually assessed using a …

Performance evaluation of supervised classification learning method related to its prediction
ability on independent data is very important in machine learning. It is also almost …

With the increase in the adoption rate of machine learning algorithms in multiple sectors, the
need for accurate measurement and assessment is imperative, especially when classifiers …

Currently for small-scale machine learning projects, there is no limit which has been set by
its researchers to categorise datasets for inexperienced users such as students while …

Evaluation metric plays a critical role in achieving the optimal classifier during the
classification training. Thus, a selection of suitable evaluation metric is an important key for …

Many performance metrics have been introduced in the literature for the evaluation of
classification performance, each of them with different origins and areas of application …

This paper gives an overview of some ways in which our understanding of performance
evaluation measures for machine-learned classifiers has improved over the last twenty …