Results 41 to 50 of about 7,765,049 (335)
Feature Selection: A Data Perspective
, 2017 Feature selection, as a data preprocessing strategy, has been proven to be effective and efficient in preparing data (especially high-dimensional data) for various data mining and machine learning problems.
Cheng, Kewei +6 more
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Threshold Adaptation for Improved Wrapper-Based Evolutionary Feature Selection
BiomimeticsFeature selection is essential for enhancing classification accuracy, reducing overfitting, and improving interpretability in high-dimensional datasets.
Uroš Mlakar, Iztok Fister, Iztok Fister
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Supervised Feature Selection With a Stratified Feature Weighting Method
IEEE Access, 2018 Feature selection has been a powerful tool to handle high-dimensional data. Most of these methods are biased toward the highest rank features which may be highly correlated with each other.
Renjie Chen +4 more
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Feature Importance in Gradient Boosting Trees with Cross-Validation Feature Selection
Entropy, 2022 Gradient Boosting Machines (GBM) are among the go-to algorithms on tabular data, which produce state-of-the-art results in many prediction tasks. Despite its popularity, the GBM framework suffers from a fundamental flaw in its base learners. Specifically,
Afek Ilay Adler, Amichai Painsky
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Online Feature Selection for Visual Tracking [PDF]
, 2016 Object tracking is one of the most important tasks in many applications of computer vision. Many tracking methods use a fixed set of features ignoring that appearance of a target object may change drastically due to intrinsic and extrinsic factors.
Melzi, Simone, Roffo, Giorgio
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Feature selection strategies: a comparative analysis of SHAP-value and importance-based methods
Journal of Big DataIn the context of high-dimensional credit card fraud data, researchers and practitioners commonly utilize feature selection techniques to enhance the performance of fraud detection models.
Huanjing Wang +3 more
semanticscholar +1 more source
Forests, 2021 Increasing numbers of explanatory variables tend to result in information redundancy and “dimensional disaster” in the quantitative remote sensing of forest aboveground biomass (AGB).
Mi Luo +6 more
semanticscholar +1 more source
Neighborhood Ranking-Based Feature Selection
IEEE AccessThis article aims to integrate ${k}$ -NN regression, false-nearest neighborhood (FNN), and trustworthiness and continuity (T&C) neighborhood-based measures into an efficient and robust feature selection method to support the identification of ...
Adam Ipkovich, Janos Abonyi
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Analysis and Evaluation of Feature Selection and Feature Extraction Methods
International Journal of Computational Intelligence Systems, 2023 Hand gestures are widely used in human-to-human and human-to-machine communication. Therefore, hand gesture recognition is a topic of great interest. Hand gesture recognition is closely related to pattern recognition, where overfitting can occur when ...
Rubén E. Nogales, Marco E. Benalcázar
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High-Dimensional Feature Selection by Feature-Wise Kernelized Lasso
, 2019 The goal of supervised feature selection is to find a subset of input features that are responsible for predicting output values. The least absolute shrinkage and selection operator (Lasso) allows computationally efficient feature selection based on ...
Bach F. +21 more
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