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An incremental approach to hierarchical feature selection by applying fuzzy rough set technique
In the age of big data, the number of class labels is increasing rapidly and there exists a hierarchical structure between different class labels. In...
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Incremental feature selection for large-scale hierarchical classification with the arrival of new samples
In the era of big data, the amount of class labels is growing rapidly, which poses a great challenge to classification tasks. The hierarchical...
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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...
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A hierarchical feature selection strategy for deepfake video detection
Digital face manipulation has become a concern in the last few years due to its harmful impacts on society. It is especially concerning for...
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Multi-view dimensionality reduction learning with hierarchical sparse feature selection
Multi-view data can depict samples from various views and learners can benefit from such complementary information, so it has attracted extensive...
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A fuzzy rough set approach to hierarchical feature selection based on Hausdorff distance
With increases in feature dimensions and the emergence of hierarchical class structures, hierarchical feature selection has become an important data...
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Feature ranking based consensus clustering for feature subset selection
Feature subset selection problem is an NP hard problem and there is a need for computationally efficient algorithms that find near optimal feature...
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Machine learning-based intrusion detection: feature selection versus feature extraction
Internet of Things (IoTs) has been playing an important role in many sectors, such as smart cities, smart agriculture, smart healthcare, and smart...
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Optimizing IoT intrusion detection system: feature selection versus feature extraction in machine learning
Internet of Things (IoT) devices are widely used but also vulnerable to cyberattacks that can cause security issues. To protect against this, machine...
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Mutual information-based filter hybrid feature selection method for medical datasets using feature clustering
Clustering is regarded as one of the most difficult tasks due to the large search space that must be explored. Feature selection aims to reduce the...
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A Feature Selection Method Based on Feature-Label Correlation Information and Self-Adaptive MOPSO
Feature selection can be seen as a multi-objective task, where the goal is to select a subset of features that exhibit minimal correlation among...
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Feature selection and clustering based web service selection using QoSs
Web Services act as a backbone to realize the smart city concept. Web service technology is useful to offer various services as part of the smart...
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Exploring advanced feature selection techniques: an application to dialectal Arabic data
In the field of automated language processing, distinguishing between Moroccan Arabic (Darija) in multilingual contexts is a major challenge. This...
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TSCL-FHFN: two-stage contrastive learning and feature hierarchical fusion network for multimodal sentiment analysis
Multimodal sentiment analysis faces two challenges: modality representation and modality fusion. Most of the existing models rely only on the feature...
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HBS–STACK: hierarchical biomarker selection and stacked ensemble model for biomarker identification and cancer prediction on multi-omics
Genomic and transcriptomic data development has provided new prospects for biomarker identification and cancer prediction. However, it is challenging...
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Finding a needle in a haystack: insights on feature selection for classification tasks
The growth of Big Data has resulted in an overwhelming increase in the volume of data available, including the number of features. Feature selection,...
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Hierarchical history based information selection for document grounded dialogue generation
Selecting appropriate information from the dialogue history and the document is a prerequisite for a high-quality response in document grounded...
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Feature selection using three-stage heuristic measures based on mutual fuzzy granularities
Mutual information is fundamental for feature selection, and relevant conditional and joint mutual fuzzy granularities (MFGs) characterize feature...
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Investigation of machine learning algorithms on heart disease through dominant feature detection and feature selection
Heart diseases are an essential research topic in healthcare institutions around the world. Therefore, using machine learning and optimization...
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Employing Feature Extraction, Feature Selection, and Machine Learning to Classify Electricity Consumption as Normal or Electricity Theft
One of the main causes of revenue loss in the energy sector across the globe has been non-technical losses. Electricity theft is a non-technical loss...
