Learning from class-imbalanced data: Review of methods and applications
Rare events, especially those that could potentially negatively impact society, often require
humans' decision-making responses. Detecting rare events can be viewed as a prediction …
humans' decision-making responses. Detecting rare events can be viewed as a prediction …
A systematic review on imbalanced data challenges in machine learning: Applications and solutions
In machine learning, the data imbalance imposes challenges to perform data analytics in
almost all areas of real-world research. The raw primary data often suffers from the skewed …
almost all areas of real-world research. The raw primary data often suffers from the skewed …
Financial credit risk assessment: a recent review
N Chen, B Ribeiro, A Chen - Artificial Intelligence Review, 2016 - Springer
The assessment of financial credit risk is an important and challenging research topic in the
area of accounting and finance. Numerous efforts have been devoted into this field since the …
area of accounting and finance. Numerous efforts have been devoted into this field since the …
Adaptive random forests with resampling for imbalanced data streams
The large volume of data generated by computer networks, smartphones, wearables and a
wide range of sensors, which produce real-time data, are only useful if they can be efficiently …
wide range of sensors, which produce real-time data, are only useful if they can be efficiently …
A genetic algorithm-based approach to cost-sensitive bankruptcy prediction
The prediction of bankruptcy is of significant importance with the present-day increase of
bankrupt companies. In the practical applications, the cost of misclassification is worthy of …
bankrupt companies. In the practical applications, the cost of misclassification is worthy of …
Multimodal Analysis of Unbalanced Dermatological Data for Skin Cancer Recognition
To date, skin cancer is the most commonly diagnosed form of cancer in humans and is one
of the leading causes of death in cancer patients. AI technologies can match and exceed …
of the leading causes of death in cancer patients. AI technologies can match and exceed …
Transcriptomic Biomarkers Associated with Microbiological Etiology and Disease Severity in Childhood Pneumonia
Background Challenges remain in discerning microbiologic etiology and disease severity in
childhood pneumonia. Defining host transcriptomic profiles during illness may facilitate …
childhood pneumonia. Defining host transcriptomic profiles during illness may facilitate …
Improving credit risk prediction in online peer-to-peer (P2P) lending using imbalanced learning techniques
Peer-to-peer (P2P) lending is a global trend of financial markets that allow individuals to
obtain and concede loans without having financial institutions as a strong proxy. As many …
obtain and concede loans without having financial institutions as a strong proxy. As many …
Optimizing Kernel Transformations to Handle Binary Class Imbalanced Dataset Classification
V Patel, H Bhavsar - Applied Artificial Intelligence, 2024 - Taylor & Francis
Imbalanced class distributions pose a prevalent challenge in numerous classification
problems, requiring effective strategies for learning from such skewed data. Traditional …
problems, requiring effective strategies for learning from such skewed data. Traditional …
Multimodal neural network system for skin cancer recognition with a modified cross-entropy loss function
P Lyakhov, U Lyakhova, D Kalita - 2023 - preprints.org
Currently, skin cancer is the most commonly diagnosed form of cancer in humans and is one
of the leading causes of death in patients with cancer. Biopsy methods are an invasive …
of the leading causes of death in patients with cancer. Biopsy methods are an invasive …