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Showing 201 - 220 results of 850 for search '(( algorithm pre function ) OR ( algorithm ((within function) OR (python function)) ))', query time: 0.37s Refine Results
  1. 201
    Confusion matrix values for different size of test samples and different choice of random states.

    Confusion matrix values for different size of test samples and different choice of random states. by Abeer Aljohani (18497914)

    Published 2025
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  2. 202
    Comparison of the results obtained with the proposed method with other methods in literature.

    Comparison of the results obtained with the proposed method with other methods in literature. by Abeer Aljohani (18497914)

    Published 2025
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  3. 203
    A comparison of the spectral component of normal and abnormal images combined with the uniform window.

    A comparison of the spectral component of normal and abnormal images combined with the uniform window. by Abeer Aljohani (18497914)

    Published 2025
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  4. 204
    A visual representation of the windows used in the study.

    A visual representation of the windows used in the study. by Abeer Aljohani (18497914)

    Published 2025
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  5. 205
    The spectral component of normal peoples and Covid-19 infected peoples.

    The spectral component of normal peoples and Covid-19 infected peoples. by Abeer Aljohani (18497914)

    Published 2025
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  6. 206
    A comparison of the original images with the filtered images with the binomial window.

    A comparison of the original images with the filtered images with the binomial window. by Abeer Aljohani (18497914)

    Published 2025
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  7. 207
    The effect of test set size and number of nodes on the values of confusion matrix using SVM combined with the uniform window.

    The effect of test set size and number of nodes on the values of confusion matrix using SVM combined with the uniform window. by Abeer Aljohani (18497914)

    Published 2025
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  8. 208
    Graphical illustration of a spectral approach for training support vector machine.

    Graphical illustration of a spectral approach for training support vector machine. by Abeer Aljohani (18497914)

    Published 2025
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  9. 209
    Accuracy of the support vector machines for different proportion of test samples and different length of nodes used for training.

    Accuracy of the support vector machines for different proportion of test samples and different length of nodes used for training. by Abeer Aljohani (18497914)

    Published 2025
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  10. 210
    Confusion matrix representation of classification outcomes.

    Confusion matrix representation of classification outcomes. by Abeer Aljohani (18497914)

    Published 2025
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  11. 211
    The parametric study of the confusion matrix values for different proportion of test samples vs number of nodes from the spectral space.

    The parametric study of the confusion matrix values for different proportion of test samples vs number of nodes from the spectral space. by Abeer Aljohani (18497914)

    Published 2025
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  12. 212
    ROC and precision plots of SVM showing the details of accuracy.

    ROC and precision plots of SVM showing the details of accuracy. by Abeer Aljohani (18497914)

    Published 2025
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  13. 213
    Classification Report of the SVM classifier without using any window.

    Classification Report of the SVM classifier without using any window. by Abeer Aljohani (18497914)

    Published 2025
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  14. 214
    Accuracy of the support vector machines for different proportion of test samples.

    Accuracy of the support vector machines for different proportion of test samples. by Abeer Aljohani (18497914)

    Published 2025
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  15. 215
    Accuracy of the proposed method using SVM combined with the uniform window.

    Accuracy of the proposed method using SVM combined with the uniform window. by Abeer Aljohani (18497914)

    Published 2025
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  16. 216
    Classification Report of the SVM classifier using a uniform window.

    Classification Report of the SVM classifier using a uniform window. by Abeer Aljohani (18497914)

    Published 2025
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  17. 217
    A. Top – 14 days of continuous glucose monitor (CGM) data for a patient that spends all of their time within an optimal glucose range.

    A. Top – 14 days of continuous glucose monitor (CGM) data for a patient that spends all of their time within an optimal glucose range. by Jamison H. Burks (21029607)

    Published 2025
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  18. 218
    Global Aridity Index and Potential Evapotranspiration (ET0) Database: Version 3.1

    Global Aridity Index and Potential Evapotranspiration (ET0) Database: Version 3.1 by Robert Zomer (12796235)

    Published 2025
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  19. 219
    Code For Use in a Bookកូដសម្រាប់ប្រើប្រាស់ក្នុងសៀវភៅ

    Code For Use in a Bookកូដសម្រាប់ប្រើប្រាស់ក្នុងសៀវភៅ by Sarun Horn (20899271)

    Published 2025
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  20. 220
    Fig 7 -

    Fig 7 - by Debao Yuan (4691992)

    Published 2024
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