A bidirectional dynamic grouping multi-objective evolutionary algorithm for feature selection on high-dimensional classification
As a key preprocessing step in classification, feature selection involves two conflicting
objectives: maximizing the classification accuracy and minimizing the number of selected …
objectives: maximizing the classification accuracy and minimizing the number of selected …
Hybrid binary COOT algorithm with simulated annealing for feature selection in high-dimensional microarray data
Microarray analysis of gene expression can help with disease and cancer diagnosis and
prognosis. Identification of gene biomarkers is one of the most difficult issues in microarray …
prognosis. Identification of gene biomarkers is one of the most difficult issues in microarray …
[HTML][HTML] Feature selection using a classification error impurity algorithm and an adaptive genetic algorithm improved with an external repository
Feature selection in small-sample high-dimensional datasets enhances classification
accuracy and reduces computational time for model training. This paper introduces the filter …
accuracy and reduces computational time for model training. This paper introduces the filter …
[HTML][HTML] Pattern recognition frequency-based feature selection with multi-objective discrete evolution strategy for high-dimensional medical datasets
H Nematzadeh, J García-Nieto… - Expert Systems with …, 2024 - Elsevier
Feature selection has a prominent role in high-dimensional datasets to increase
classification accuracy, decrease the learning algorithm computational time, and present the …
classification accuracy, decrease the learning algorithm computational time, and present the …
[HTML][HTML] Improved Swarm Intelligence Optimization Model with Mutual Information Estimation for Feature Selection in Microarray Bioinformatics Datasets for Diseases …
PR Krishna, P Rajarajeswari - International Journal of Fuzzy Logic and …, 2023 - ijfis.org
Bioinformatics has emerged as a promising field with innovative applications in various
biological domains. Microarray data analysis has become the preferred technology for …
biological domains. Microarray data analysis has become the preferred technology for …
Feature selection of microarray data using multidimensional graph neural network and supernode hierarchical clustering
Cancer remains a significant cause of mortality, and the application of microarray technology
has opened new avenues for cancer diagnosis and treatment. However, due to the …
has opened new avenues for cancer diagnosis and treatment. However, due to the …
A Hybrid Feature Selection Method Based on Binary Differential Evolution and Feature Subset Correlation for Microarray Data
Obtaining essential genes from microarray data that can diagnose diseases can be very
useful for researchers to understand diseases and develop drugs. However, the high …
useful for researchers to understand diseases and develop drugs. However, the high …
A hybrid feature selection method for biomarker identification
M Wang, M Zhao, W Xie - Fourth International Conference on …, 2024 - spiedigitallibrary.org
Identifying disease-specific biomarkers from gene microarray data is crucial for disease
diagnosis. Genetic algorithms can effectively select important features through efficient …
diagnosis. Genetic algorithms can effectively select important features through efficient …