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OpenAlex konusu

Machine Learning and Data Classification

Bu sayfa OpenAlex konu etiketine göre çalışmaları ve o konuda görünen akademisyenleri listeler. YÖKSİS temel alan / yan dal değildir.

OpenAlex 1.114 eser 34 yazar konusu

Çalışmalar

1.114 eser

  1. Fast Kernel Classifiers With Online And Active Learning 2005
    OpenAlex üst %1 OpenAlex 99.8%

    International audience

  2. Introduction to Machine Learning 2013
    OpenAlex üst %10 OpenAlex 97.9%

    The machine learning field, which can be briefly defined as enabling computers make successful predictions using past experiences, has exhibited an impressive development recently with the help of the rapid increase in the storage capacity and processing power of computers. Together with many other disciplines, machin…

  3. A hybrid approach of differential evolution and artificial bee colony for feature selection 2016
    YÖKSİS SJR Q1 JCR Q1 OpenAlex üst %1 OpenAlex 99.8%

    Özet henüz yok.

  4. Image classification with deep learning in the presence of noisy labels: A survey 2021
    YÖKSİS SJR Q1 JCR Q1 OpenAlex üst %1 OpenAlex 99.8%

    Özet henüz yok.

  5. Learning differential diagnosis of erythemato-squamous diseases using voting feature intervals 1998
    OpenAlex üst %10 OpenAlex 92.8%

    Özet henüz yok.

  6. Learning Differential Diagnosis of Erythemato Squamous Diseases using Voting Feature Intervals 1998
    YÖKSİS SJR Q2 JCR Q2 OpenAlex üst %10 OpenAlex 96.3%

    Özet henüz yok.

  7. Tuning Hyperparameters of Machine Learning Algorithms and Deep Neural Networks Using Metaheuristics: A Bioinformatics Study on Biomedical and Biological Cases 2022
    YÖKSİS SJR Q2 JCR Q2 OpenAlex üst %1 OpenAlex 99.4%

    Özet henüz yok.

  8. Tuning Hyperparameters of Machine Learning Algorithms and Deep Neural Networks Using Metaheuristics: A Bioinformatics Study on Biomedical and Biological Cases 2022
    YÖKSİS SJR Q2 JCR Q2 OpenAlex üst %1 OpenAlex 99.4%

    Özet henüz yok.

  9. The Effect of the Normalization Method Used in Different Sample Sizes on the Success of Artificial Neural Network Model 2019
    OpenAlex üst %10 OpenAlex 97.9%

    In this study, it was aimed to compare different normalization methods employed in model developing process via artificial neural networks with different sample sizes. As part of comparison of normalization methods, input variables were set as: work discipline, environmental awareness, instrumental motivation, science…

  10. The Effect of the Normalization Method Used in Different Sample Sizes on the Success of Artificial Neural Network Model 2019
    YÖKSİS TR Index JCR Q3 OpenAlex üst %10 OpenAlex 97.9%

    In this study, it was aimed to compare different normalization methods employed in model developing process via artificial neural networks with different sample sizes. As part of comparison of normalization methods, input variables were set as: work discipline, environmental awareness, instrumental motivation, science…

  11. A fuzzy-rough nearest neighbor classifier combined with consistency-based subset evaluation and instance selection for automated diagnosis of breast cancer 2015
    YÖKSİS SJR Q1 JCR Q1 OpenAlex üst %1 OpenAlex 99.1%

    Özet henüz yok.

  12. Data oversampling and imbalanced datasets: an investigation of performance for machine learning and feature engineering 2024
    YÖKSİS SJR Q1 JCR Q1 OpenAlex üst %1 OpenAlex 99.9%

    Abstract The classification of imbalanced datasets is a prominent task in text mining and machine learning. The number of samples in each class is not uniformly distributed; one class contains a large number of samples while the other has a small number. Overfitting of the model occurs as a result of imbalanced datase…

Akademisyenler

34 akademisyen