Mar 25, 2015 · In this research, a combined technique, called Soft-Hybrid algorithm, was proposed for improving classification performance.
In this paper, a Soft-Hybrid algorithm with low computational time complexity under the newly studied aspect was introduced. Extracting all obviously non- ...
Oct 22, 2024 · In this research, a combined technique, called Soft-Hybrid algorithm, was proposed for improving classification performance. The technique was ...
Improving classification rate constrained to imbalanced data between overlapped and non-overlapped regions by hybrid algorithms[J]. Neurocomputing, 2015 ...
Dec 10, 2022 · This study proposes a Tomek link and genetic algorithm (GA)-based under-sampling framework (TEUS) to address the class imbalance and overlap issues in binary ...
This research study proposes a hybrid approach that combines both data level balancing and algorithm level tuning methods to create a cost associated ...
A quantum-based oversampling method for classification of highly ...
journals.sagepub.com › doi › abs
Jan 28, 2024 · In this article, we propose a novel quantum-based oversampling method (QOSM) to effectively tackle data imbalance and class overlapping, thereby improving ...
Lursinsap, Improving classification rate constrained to imbalanced data between overlapped and non-overlapped regions by hybrid algorithms, Neurocomputing ...
Jan 28, 2024 · In this article, we propose a novel quantum-based oversampling method (QOSM) to effectively tackle data imbalance and class overlapping, thereby improving ...
In this paper we propose an adaptive multiple classifier system named of AMCS to cope with multi-class imbalanced learning, which makes a distinction among ...