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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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Intelligent Feature Selection Methods: A Survey [PDF]
Engineering and Technology Journal, 2021 Consider feature selection is the main in intelligent algorithms and machine learning to select the subset of data to help acquire the optimal solution.
Noor Jameel, Hasanen S. Abdullah
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A niching memetic algorithm for simultaneous clustering and feature selection [PDF]
, 2008 Clustering is inherently a difficult task, and is made even more difficult when the selection of relevant features is also an issue. In this paper we propose an approach for simultaneous clustering and feature selection using a niching memetic algorithm.
Fairhurst, M, Liu, X, Sheng, W
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Feature selection on quantum computers
Quantum Machine Intelligence, 2023 AbstractIn machine learning, fewer features reduce model complexity. Carefully assessing the influence of each input feature on the model quality is therefore a crucial preprocessing step. We propose a novel feature selection algorithm based on a quadratic unconstrained binary optimization (QUBO) problem, which allows to select a specified number of ...
Sascha Mücke +4 more
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Semi-supervised Partial Multi-label Feature Selection [PDF]
Jisuanji kexueMulti-label feature selection is a technique for reducing feature dimensionality by filtering out a subset of features with distinguishing power from the original feature space.However,the traditional method faces the problem of labeling accuracy ...
WU You, WANG Jing, LI Peipei, HU Xuegang
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CBFS: high performance feature selection algorithm based on feature clearness. [PDF]
PLoS ONE, 2012 BACKGROUND: The goal of feature selection is to select useful features and simultaneously exclude garbage features from a given dataset for classification purposes.
Minseok Seo, Sejong Oh
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Feature selection in jump models [PDF]
Expert Systems with Applications, 2021 Jump models switch infrequently between states to fit a sequence of data while taking the ordering of the data into account. We propose a new framework for joint feature selection, parameter and state-sequence estimation in jump models. Feature selection is necessary in high-dimensional settings where the number of features is large compared to the ...
Peter Nystrup +3 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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Improving feature selection algorithms using normalised feature histograms
, 2011 The proposed feature selection method builds a histogram of the most stable features from random subsets of a training set and ranks the features based on a classifier based cross-validation.
A.K. Maan, A.P. James, Fan, Hall
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ACM Computing Surveys, 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. The objectives of feature selection include building simpler and more comprehensible models, improving data-mining performance, and preparing clean,
Jundong Li +6 more
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