Online detection of class-imbalanced error-related potentials evoked by motor imagery
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Neural Engineering"
DOI: 10.1088/1741-2552/abf522
Abstract: Objective. Error-related potentials (ErrPs) are spontaneous electroencephalogram signals related to the awareness of erroneous responses within brain domain. ErrPs-based correction mechanisms can be applied to motor imagery-brain–computer interface (MI-BCI) to prevent incorrect actions and ultimately… read more here.
Keywords: class imbalanced; detection; classification; class ... See more keywords
Multiple Filter-Based Rankers to Guide Hybrid Grasshopper Optimization Algorithm and Simulated Annealing for Feature Selection With High Dimensional Multi-Class Imbalanced Datasets
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3081366
Abstract: DNA microarray data analysis is infamous due to a massive number of features, imbalanced class distribution, and limited available samples. In this paper, we focus on high-dimensional multi-class imbalanced problems. The high dimensional and multi-class… read more here.
Keywords: class imbalanced; high dimensional; class; multi class ... See more keywords
Active Broad-Transfer Learning Algorithm for Class-Imbalanced Fault Diagnosis
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2022.3227995
Abstract: Knowledge transfer with class-imbalanced data is a challenge in predictive maintenance and fault diagnosis. Deep learning algorithms have provided promising results in fault diagnosis. However, their prediction performance is affected by class-imbalanced data in cross-domain… read more here.
Keywords: fault diagnosis; class imbalanced; active broad; class ... See more keywords
A Weakly Supervised Learning-Based Oversampling Framework for Class-Imbalanced Fault Diagnosis
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Reliability"
DOI: 10.1109/tr.2021.3138448
Abstract: With the lack of failure data, class imbalance has become a common challenge in the fault diagnosis of industrial systems. The oversampling methods can tackle the class-imbalanced problem by generating the minority samples to balance… read more here.
Keywords: synthetic samples; fault diagnosis; class imbalanced; framework ... See more keywords
A comparative study on class-imbalanced gas turbine fault diagnosis
Sign Up to like & getrecommendations! Published in 2022 at "Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering"
DOI: 10.1177/09544100221107252
Abstract: Gas turbines are widely used in various fields, and the failure of gas turbines can cause catastrophic consequences. Health condition monitoring and fault diagnosis of gas turbines can detect faults timely, avoid serious faults, and… read more here.
Keywords: gas; fault diagnosis; class imbalanced; diagnosis ... See more keywords
Boosting methods for multi-class imbalanced data classification: an experimental review
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Big Data"
DOI: 10.1186/s40537-020-00349-y
Abstract: Since canonical machine learning algorithms assume that the dataset has equal number of samples in each class, binary classification became a very challenging task to discriminate the minority class samples efficiently in imbalanced datasets. For… read more here.
Keywords: class imbalanced; imbalanced data; classification; class ... See more keywords
An oversampling method for multi-class imbalanced data based on composite weights
Sign Up to like & getrecommendations! Published in 2021 at "PLoS ONE"
DOI: 10.1371/journal.pone.0259227
Abstract: To solve the oversampling problem of multi-class small samples and to improve their classification accuracy, we develop an oversampling method based on classification ranking and weight setting. The designed oversampling algorithm sorts the data within… read more here.
Keywords: class imbalanced; imbalanced data; class; multi class ... See more keywords
Addressing Binary Classification over Class Imbalanced Clinical Datasets Using Computationally Intelligent Techniques
Sign Up to like & getrecommendations! Published in 2022 at "Healthcare"
DOI: 10.3390/healthcare10071293
Abstract: Nowadays, healthcare is the prime need of every human being in the world, and clinical datasets play an important role in developing an intelligent healthcare system for monitoring the health of people. Mostly, the real-world… read more here.
Keywords: class imbalanced; clinical datasets; class; imbalanced clinical ... See more keywords
Feature Ranking and Screening for Class-Imbalanced Metabolomics Data Based on Rank Aggregation Coupled with Re-Balance
Sign Up to like & getrecommendations! Published in 2021 at "Metabolites"
DOI: 10.3390/metabo11060389
Abstract: Feature screening is an important and challenging topic in current class-imbalance learning. Most of the existing feature screening algorithms in class-imbalance learning are based on filtering techniques. However, the variable rankings obtained by various filtering… read more here.
Keywords: class; class imbalanced; feature; rank aggregation ... See more keywords