(AF)2-S3Net: Attentive Feature Fusion with Adaptive Feature Selection for Sparse Semantic Segmentation Network [PDF]
Computer Vision and Pattern Recognition, 2021 Autonomous robotic systems and self driving cars rely on accurate perception of their surroundings as the safety of the passengers and pedestrians is the top priority. Semantic segmentation is one of the essential components of road scene perception that
Ran Cheng +4 more
semanticscholar +1 more source
Shapley values for feature selection: The good, the bad, and the axioms [PDF]
IEEE Access, 2021 The Shapley value has become popular in the Explainable AI (XAI) literature, thanks, to a large extent, to a solid theoretical foundation, including four “favourable and fair” axioms for attribution in transferable utility games.
D. Fryer, Inga Strümke, Hien Nguyen
semanticscholar +1 more source
Survey of feature selection and extraction techniques for stock market prediction
Financial Innovation, 2023 In stock market forecasting, the identification of critical features that affect the performance of machine learning (ML) models is crucial to achieve accurate stock price predictions.
Htet Htet Htun, Michael Biehl, N. Petkov
semanticscholar +1 more source
Adapting Feature Selection Algorithms for the Classification of Chinese Texts
Syst., 2023 Text classification has been highlighted as the key process to organize online texts for better communication in the Digital Media Age. Text classification establishes classification rules based on text features, so the accuracy of feature selection is ...
Xuan Liu +7 more
semanticscholar +1 more source
A Review of Feature Selection Methods for Machine Learning-Based Disease Risk Prediction
Frontiers in Bioinformatics, 2022 Machine learning has shown utility in detecting patterns within large, unstructured, and complex datasets. One of the promising applications of machine learning is in precision medicine, where disease risk is predicted using patient genetic data. However,
N. Pudjihartono +3 more
semanticscholar +1 more source
Metaheuristic Algorithms on Feature Selection: A Survey of One Decade of Research (2009-2019)
IEEE Access, 2021 Feature selection is a critical and prominent task in machine learning. To reduce the dimension of the feature set while maintaining the accuracy of the performance is the main aim of the feature selection problem.
Prachi Agrawal +3 more
semanticscholar +1 more source
Multiclass feature selection with metaheuristic optimization algorithms: a review
Neural computing & applications (Print), 2022 Selecting relevant feature subsets is vital in machine learning, and multiclass feature selection is harder to perform since most classifications are binary.
Olatunji Akinola +4 more
semanticscholar +1 more source
Stable Feature Selection for Biomarker Discovery [PDF]
, 2010 Feature selection techniques have been used as the workhorse in biomarker discovery applications for a long time. Surprisingly, the stability of feature selection with respect to sampling variations has long been under-considered.
He, Zengyou, Yu, Weichuan
core +2 more sources
EFSIS: Ensemble Feature Selection Integrating Stability [PDF]
, 2018 Ensemble learning that can be used to combine the predictions from multiple learners has been widely applied in pattern recognition, and has been reported to be more robust and accurate than the individual learners.
Jonassen, Inge, Zhang, Xiaokang
core +2 more sources
Optimization for Gene Selection and Cancer Classification
Proceedings, 2021 Recently, gene selection has played an important role in cancer diagnosis and classification. In this study, it was studied to select high descriptive genes for use in cancer diagnosis in order to develop a classification analysis for cancer diagnosis ...
Hülya Başeğmez +2 more
doaj +1 more source