172 citations · 203 across the 7 of their papers we have counts for
5 papers · 1 filter
EasyClassifier: Honest, Reproducible Machine-Learning Classification for Researchers Who Do Not Program
Ahmad B. A. Hassanat, Ghada A. Altarawneh
Machine-learning classification is now used across medicine, the social sciences, economics, education and engineering, very often by researchers who do not program. Two errors rec…
Synthetic minority data is redundant or invalid: a data-dependent validity theory and a de-biased test
Ahmad B. Hassanat, Ahmad S. Tarawneh, Ghada A. Altarawneh
For two decades, the standard remedy for class-imbalanced learning has been to fabricate synthetic minority examples, and the standard evidence of their validity has been a check t…
Stop Oversampling for Class Imbalance Learning: A Critical Review
Ahmad B. Hassanat, Ahmad S. Tarawneh, Ghada A. Altarawneh +1
For the last two decades, oversampling has been employed to overcome the challenge of learning from imbalanced datasets. Many approaches to solving this challenge have been offered…
On Enhancing The Performance Of Nearest Neighbour Classifiers Using Hassanat Distance Metric
Mouhammd Alkasassbeh, Ghada A. Altarawneh, Ahmad B. A. Hassanat
We showed in this work how the Hassanat distance metric enhances the performance of the nearest neighbour classifiers. The results demonstrate the superiority of this distance metr…
Solving the Problem of the K Parameter in the KNN Classifier Using an Ensemble Learning Approach
Ahmad Basheer Hassanat, Mohammad Ali Abbadi, Ghada Awad Altarawneh +1
This paper presents a new solution for choosing the K parameter in the k-nearest neighbor (KNN) algorithm, the solution depending on the idea of ensemble learning, in which a weak…