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Showing 1 - 20 results of 99 for search 'feature selection algorithm', query time: 0.08s Refine Results
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    Nested ensemble selection: An effective hybrid feature selection method by Kamalov, Firuz

    Published 2023
    “…It has been shown that while feature selection algorithms are able to distinguish between relevant and irrelevant features, they fail to differentiate between relevant and redundant and correlated features. …”
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    Intelligent Hybrid Feature Selection for Textual Sentiment Classification by Jawad Khan (6422669)

    Published 2021
    “…Effective feature extraction and selection are significant for the SA because they can boost the learning algorithm’s predictive performance while reducing the high-dimensional feature space. …”
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    Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

    Published 2025
    “…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …”
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    Reinforced steering Evolutionary Markov Chain for high-dimensional feature selection by Atiq ur Rehman (3044409)

    Published 2024
    “…Although Evolutionary Algorithms (EAs) have shown promise in the literature for feature selection, creating EAs for high dimensions is still challenging. …”
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    Machine learning approach for the classification of corn seed using hybrid features by Aqib Ali (19680145)

    Published 2020
    “…The nine optimized features have been acquired by employing the correlation-based feature selection (CFS) technique with the Best First search algorithm. …”
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    An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection by Abu Zitar, Raed

    Published 2022
    “…In this paper, an enhanced binary version of the Rat Swarm Optimizer (RSO) is proposed to deal with Feature Selection (FS) problems. FS is an important data reduction step in data mining which finds the most representative features from the entire data. …”
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    A feature‐based approach for guiding the selection of Internet of Things cybersecurity standards using text mining by Koen Schaaf (14778139)

    Published 2021
    “…First, the common and variant features of IoT cybersecurity have been modeled using a feature model. …”