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   Articles with "selection methods" as a keyword



Comparing two recurrent selection methods for developing superior apomictic hybrids in Paspalum notatum

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recommendations! Published in 2024 at "Crop Science"

DOI: 10.1002/csc2.21270

Abstract: Recurrent selection methods have been successful in generating superior Paspalum notatum families through the accumulation of favorable alleles. However, the effectiveness of these methods in producing apomictic hybrids with superior agronomic traits has not been… read more here.

Keywords: recurrent selection; apomictic hybrids; selection methods; paspalum notatum ... See more keywords

A systematic review and evaluation of statistical methods for group variable selection

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recommendations! Published in 2022 at "Statistics in Medicine"

DOI: 10.1002/sim.9620

Abstract: This review condenses the knowledge on variable selection methods implemented in R and appropriate for datasets with grouped features. The focus is on regularized regressions identified through a systematic review of the literature, following the… read more here.

Keywords: review; group; methods group; selection methods ... See more keywords

An empirical evaluation of hierarchical feature selection methods for classification in bioinformatics datasets with gene ontology-based features

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recommendations! Published in 2017 at "Artificial Intelligence Review"

DOI: 10.1007/s10462-017-9541-y

Abstract: Hierarchical feature selection is a new research area in machine learning/data mining, which consists of performing feature selection by exploiting dependency relationships among hierarchically structured features. This paper evaluates four hierarchical feature selection methods, i.e.,… read more here.

Keywords: hierarchical feature; selection methods; ontology; feature selection ... See more keywords

Towards Exploring the Limitations of Test Selection Techniques on Graph Neural Networks: An Empirical Study

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recommendations! Published in 2024 at "Empirical Software Engineering"

DOI: 10.1007/s10664-024-10515-y

Abstract: Graph Neural Networks (GNNs) have gained prominence in various domains, such as social network analysis, recommendation systems, and drug discovery, due to their ability to model complex relationships in graph-structured data. GNNs can exhibit incorrect… read more here.

Keywords: empirical study; selection methods; test; selection ... See more keywords

A review of feature selection methods in medical applications

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recommendations! Published in 2019 at "Computers in biology and medicine"

DOI: 10.1016/j.compbiomed.2019.103375

Abstract: Feature selection is a preprocessing technique that identifies the key features of a given problem. It has traditionally been applied in a wide range of problems that include biological data processing, finance, and intrusion detection… read more here.

Keywords: feature selection; methods medical; selection; medical applications ... See more keywords

Feature selection for the classification of traced neurons

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recommendations! Published in 2018 at "Journal of Neuroscience Methods"

DOI: 10.1016/j.jneumeth.2018.04.002

Abstract: BACKGROUND The great availability of computational tools to calculate the properties of traced neurons leads to the existence of many descriptors which allow the automated classification of neurons from these reconstructions. This situation determines the… read more here.

Keywords: classification; feature selection; selection; traced neurons ... See more keywords

Theoretical foundations of forward feature selection methods based on mutual information

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recommendations! Published in 2019 at "Neurocomputing"

DOI: 10.1016/j.neucom.2018.09.077

Abstract: Abstract Feature selection problems arise in a variety of applications, such as microarray analysis, clinical prediction, text categorization, image classification and face recognition, multi-label learning, and classification of internet traffic. Among the various classes of… read more here.

Keywords: forward feature; feature selection; based mutual; selection methods ... See more keywords

Benchmarking feature selection methods for compressing image information in high-content screening.

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recommendations! Published in 2021 at "SLAS technology"

DOI: 10.1016/j.slast.2021.10.015

Abstract: Biopharmaceutical drug discovery, as of today is a highly automated, high throughput endeavor, where many screening technologies produce a high-dimensional measurement per sample. A striking example is High Content Screening (HCS), which utilizes automated microscopy… read more here.

Keywords: high content; feature; information; selection methods ... See more keywords
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Inferring the Main Drivers of SARS‐CoV‐2 Global Transmissibility by Feature Selection Methods

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recommendations! Published in 2021 at "GeoHealth"

DOI: 10.1029/2021gh000432

Abstract: Identifying the main environmental drivers of SARS‐CoV‐2 transmissibility in the population is crucial for understanding current and potential future outbursts of COVID‐19 and other infectious diseases. To address this problem, we concentrate on the basic… read more here.

Keywords: selection methods; drivers sars; feature selection; transmissibility ... See more keywords

Comparison of models and visualization of total volatile basic nitrogen content in mutton using hyperspectral imaging and variable selection methods

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recommendations! Published in 2018 at "Spectroscopy Letters"

DOI: 10.1080/00387010.2018.1452268

Abstract: ABSTRACT Hyperspectral imaging combined with variable selection methods was used to perform the rapid and accurate detection and visualization of total volatile basic nitrogen content in mutton. For each sample, several spectra were extracted from… read more here.

Keywords: hyperspectral imaging; visualization total; model; variable selection ... See more keywords

Stochastic feature selection with annealing and its applications to streaming data

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recommendations! Published in 2025 at "Journal of Nonparametric Statistics"

DOI: 10.1080/10485252.2025.2456767

Abstract: Feature selection is an important topic in high-dimensional statistics and machine learning, for prediction and understanding the underlying phenomena. It has many applications in computer vision, natural language processing, bioinformatics, etc. However, most feature selection… read more here.

Keywords: stochastic feature; selection methods; proposed methods; selection ... See more keywords