A review of the F-measure: its history, properties, criticism, and alternatives
Methods to classify objects into two or more classes are at the core of various disciplines.
When a set of objects with their true classes is available, a supervised classifier can be …
When a set of objects with their true classes is available, a supervised classifier can be …
Extract interpretability-accuracy balanced rules from artificial neural networks: A review
Artificial neural networks (ANN) have been widely used and have achieved remarkable
achievements. However, neural networks with high accuracy and good performance often …
achievements. However, neural networks with high accuracy and good performance often …
Machine learning: new ideas and tools in environmental science and engineering
The rapid increase in both the quantity and complexity of data that are being generated daily
in the field of environmental science and engineering (ESE) demands accompanied …
in the field of environmental science and engineering (ESE) demands accompanied …
The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation
Background To evaluate binary classifications and their confusion matrices, scientific
researchers can employ several statistical rates, accordingly to the goal of the experiment …
researchers can employ several statistical rates, accordingly to the goal of the experiment …
Multiple skin lesions diagnostics via integrated deep convolutional networks for segmentation and classification
Background and objective Computer automated diagnosis of various skin lesions through
medical dermoscopy images remains a challenging task. Methods In this work, we propose …
medical dermoscopy images remains a challenging task. Methods In this work, we propose …
Learning fair representations for recommendation: A graph-based perspective
As a key application of artificial intelligence, recommender systems are among the most
pervasive computer aided systems to help users find potential items of interests. Recently …
pervasive computer aided systems to help users find potential items of interests. Recently …
A deep learning based traffic crash severity prediction framework
Highway work zones are most vulnerable roadway segments for congestion and traffic
collisions. Hence, providing accurate and timely prediction of the severity of traffic collisions …
collisions. Hence, providing accurate and timely prediction of the severity of traffic collisions …
LSTM and bat-based RUSBoost approach for electricity theft detection
The electrical losses in power systems are divided into non-technical losses (NTLs) and
technical losses (TLs). NTL is more harmful than TL because it includes electricity theft …
technical losses (TLs). NTL is more harmful than TL because it includes electricity theft …
F*: an interpretable transformation of the F-measure
The F-measure, also known as the F1-score, is widely used to assess the performance of
classification algorithms. However, some researchers find it lacking in intuitive interpretation …
classification algorithms. However, some researchers find it lacking in intuitive interpretation …
Classification of garments from fashion MNIST dataset using CNN LeNet-5 architecture
Recently, deep learning has been used extensively in a wide range of domains. A class of
deep neural networks that give the most rigorous effects in solving real-world problems is a …
deep neural networks that give the most rigorous effects in solving real-world problems is a …