Results 21 to 30 of about 642,813 (313)
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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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 Selection Using Neighborhood based Entropy [PDF]
Journal of Universal Computer Science, 2022 Feature selection plays an important role as a preprocessing step for pattern recognition and machine learning. The goal of feature selection is to determine an optimal subset of relevant features out of a large number of features.
Fatemeh Farnaghi-Zadeh +2 more
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Procedia Computer Science, 2016 AbstractFeature selection, as a dimensionality reduction technique, aims to choosing a small subset of the relevant features from the original features by removing irrelevant, redundant or noisy features. Feature selection usually can lead to better learning performance, i.e., higher learning accuracy, lower computational cost, and better model ...
Lingfeng Niu, Jianyu Miao
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A feature selection method with feature ranking using genetic programming
Connection Science, 2022 Feature selection is a data processing method which aims to select effective feature subsets from original features. Feature selection based on evolutionary computation (EC) algorithms can often achieve better classification performance because of their ...
Guopeng Liu +3 more
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Utility metric for unsupervised feature selection [PDF]
PeerJ Computer Science, 2021 Feature selection techniques are very useful approaches for dimensionality reduction in data analysis. They provide interpretable results by reducing the dimensions of the data to a subset of the original set of features.
Amalia Villa +4 more
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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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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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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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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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