Android applications are developing rapidly across the mobile ecosystem, but Android
malware is also emerging in an endless stream. Many researchers have studied the …

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 …

The field of machine learning has matured to the point where many sophisticated learning
approaches can be applied to practical applications. Thus it is of critical importance that …

This paper presents a systematic analysis of twenty four performance measures used in the
complete spectrum of Machine Learning classification tasks, ie, binary, multi-class, multi …

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 …

The world continues to generate quintillion bytes of data daily, leading to the pressing needs
for new efforts in dealing with the grand challenges brought by Big Data. Today, there is a …

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

Machine learning algorithms such as genetic programming (GP) can evolve biased
classifiers when data sets are unbalanced. Data sets are unbalanced when at least one …

This paper proposes a systematic benchmarking method called BenchMetrics to analyze
and compare the robustness of binary classification performance metrics based on the …

The evaluation of classification performance is crucial for algorithm and model selection.
However, a performance measure for multiclass classification problems (ie, more than two …