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justification » purification (Viiddit ozu), certification (Viiddit ozu)
Čájehuvvojit 281 - 300 oktiibuot 11 828 bohtosis ohcui ((((notifications OR notifications) OR justification) OR modification) OR classification)', ohcanáigi: 0,14s Aiddostahte ozu
  1. 281

    SVM classification precision scores. Dahkki Alina Troglio (13165866)

    Almmustuhtton 2025
    “…<p>Precision values for SVM classification, provided as a CSV file with comma-separated values.…”
  2. 282

    Performance of lesion classification studies. Dahkki Arianna Bunnell (18213784)

    Almmustuhtton 2025
    “…<p>Scatter plot showing reported performance (as measured by AUROC) for lesion classification (interpretation) studies against the reported size of the development dataset by number of breast ultrasound images. …”
  3. 283

    Features used for diagnosis classification. Dahkki Pénélope Pelland-Goulet (20597900)

    Almmustuhtton 2025
    “…All cells left white did not contribute to classification. The characteristic features for the neurotypical control group can be obtained by simply multiplying the feature values shown here by −1.…”
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  12. 292

    Dendrogram classification of environmental variables. Dahkki Abduljamiu Olalekan Amao (14836876)

    Almmustuhtton 2025
    “…<p>Dendrogram classification of environmental variables.</p>…”
  13. 293

    Classification of attributes in the studies examined. Dahkki Olivier Touzé (22133040)

    Almmustuhtton 2025
    “…<p>Classification of attributes in the studies examined.</p>…”
  14. 294
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  16. 296

    Classification performance model comparison. Dahkki Line Kruse (22305380)

    Almmustuhtton 2025
    “…<p>Performance of the five classification models on training set (black lines) and test set (colored bars) evaluated on A) F1 scores and B) ROC-AUC scores.…”
  17. 297
  18. 298

    LLM argument classification results Dahkki Filip Gampel (22074140)

    Almmustuhtton 2025
    “…<p dir="ltr">The datasets contain the results of prompting various LLM's with the goal of argument classification. For details see https://arxiv.org/abs/2507.08621</p>…”
  19. 299
  20. 300

    Classification of bearing data labels. Dahkki Hongwei Bai (1447999)

    Almmustuhtton 2025
    “…To address this issue, this paper proposes an improved parallel one-dimensional convolutional neural network model, which integrates a parallel dual-channel convolutional kernel, a gated recurrent unit, and an attention mechanism. The classification is performed using a global max-pooling layer followed by a Softmax layer. …”