Many real-world classification problems are significantly class-imbalanced to detriment of the class of interest. The standard set of proper evaluation metrics is well-known but the …
Abstract Machine learning algorithms have successfully entered industry through many real- world applications (eg, search engines and product recommendations). In these …
F Provost, R Kohavi - MACHINE LEARNING-BOSTON-, 1998 - ai.stanford.edu
Common arguments for including applications papers in the Machine Learning literature are often based on the papers' value for advertising success stories and for morale boosting. For …
T Jo, N Japkowicz - ACM Sigkdd Explorations Newsletter, 2004 - dl.acm.org
It is often assumed that class imbalances are responsible for significant losses of performance in standard classifiers. The purpose of this paper is to the question whether …
B Juba, HS Le - Proceedings of the AAAI conference on artificial …, 2019 - ojs.aaai.org
Practitioners of data mining and machine learning have long observed that the imbalance of classes in a data set negatively impacts the quality of classifiers trained on that data …
P Flach - Proceedings of the AAAI conference on artificial …, 2019 - aaai.org
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 …
C Drummond, RC Holte - … on learning from imbalanced datasets II, 2003 - eiti.uottawa.ca
This paper takes a new look at two sampling schemes commonly used to adapt machine learning algorithms to imbalanced classes and misclassification costs. It uses a performance …
W Zheng, M Jin - SN Computer Science, 2020 - Springer
This study discusses the effects of class imbalance and training data size on the predictive performance of classifiers. An empirical study was performed on ten classifiers arising from …
Cross-validation is a very commonly employed technique used to evaluate classifier performance. However, it can potentially introduce dataset shift, a harmful factor that is often …