AltWOA: Altruistic Whale Optimization Algorithm for feature selection on microarray datasets
The data-driven modern era has enabled the collection of large amounts of biomedical and
clinical data. DNA microarray gene expression datasets have mainly gained significant …
clinical data. DNA microarray gene expression datasets have mainly gained significant …
Binary aquila optimizer for selecting effective features from medical data: A COVID-19 case study
Medical technological advancements have led to the creation of various large datasets with
numerous attributes. The presence of redundant and irrelevant features in datasets …
numerous attributes. The presence of redundant and irrelevant features in datasets …
Radiogenomic classification for MGMT promoter methylation status using multi-omics fused feature space for least invasive diagnosis through mpMRI scans
Accurate radiogenomic classification of brain tumors is important to improve the standard of
diagnosis, prognosis, and treatment planning for patients with glioblastoma. In this study, we …
diagnosis, prognosis, and treatment planning for patients with glioblastoma. In this study, we …
Towards unbiased and accurate deferral to multiple experts
Machine learning models are often implemented in cohort with humans in the pipeline, with
the model having an option to defer to a domain expert in cases where it has low confidence …
the model having an option to defer to a domain expert in cases where it has low confidence …
Improvement of Bagging performance for classification of imbalanced datasets using evolutionary multi-objective optimization
Today, classification of imbalanced datasets, in which the samples belonging to one class is
more than the samples pertaining to other classes, has been paid much attention owing to …
more than the samples pertaining to other classes, has been paid much attention owing to …
CDBH: A clustering and density-based hybrid approach for imbalanced data classification
The problem of imbalanced data set classification is prevalent in the studies of machine
learning and data mining. In these kinds of data sets, the number of samples in classes is …
learning and data mining. In these kinds of data sets, the number of samples in classes is …
Understanding the apparent superiority of over-sampling through an analysis of local information for class-imbalanced data
Data plays a key role in the design of expert and intelligent systems and therefore, data
preprocessing appears to be a critical step to produce high-quality data and build accurate …
preprocessing appears to be a critical step to produce high-quality data and build accurate …
A memetic algorithm using emperor penguin and social engineering optimization for medical data classification
Gene selection and classification of microarray data play an important role in cancer
diagnosis and treatment. One of the most popular and faster classification model is support …
diagnosis and treatment. One of the most popular and faster classification model is support …
A fast and accurate approach for bankruptcy forecasting using squared logistics loss with GPU-based extreme gradient boosting
Over the last two decades, the diagnosis of bankruptcy firms has become extremely
important to business owners, banks, governments, securities investors, and economic …
important to business owners, banks, governments, securities investors, and economic …
A new clustering mining algorithm for multi-source imbalanced location data
L Cai, H Wang, F Jiang, Y Zhang, Y Peng - Information Sciences, 2022 - Elsevier
In the era of big data, clustering based on multi-source data fusion has become a hot topic in
data mining field. Existing studies mainly focus on fusion models and algorithms of data sets …
data mining field. Existing studies mainly focus on fusion models and algorithms of data sets …