بدائل البحث:
bayesian optimization » based optimization (توسيع البحث)
detection algorithms » detection algorithm (توسيع البحث), genetic algorithms (توسيع البحث)
learning detection » learning prediction (توسيع البحث), enabling detection (توسيع البحث), learning predictions (توسيع البحث)
data learning » meta learning (توسيع البحث), deep learning (توسيع البحث), a learning (توسيع البحث)
task bayesian » a bayesian (توسيع البحث), art bayesian (توسيع البحث), pac bayesian (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
binary task » binary mask (توسيع البحث)
bayesian optimization » based optimization (توسيع البحث)
detection algorithms » detection algorithm (توسيع البحث), genetic algorithms (توسيع البحث)
learning detection » learning prediction (توسيع البحث), enabling detection (توسيع البحث), learning predictions (توسيع البحث)
data learning » meta learning (توسيع البحث), deep learning (توسيع البحث), a learning (توسيع البحث)
task bayesian » a bayesian (توسيع البحث), art bayesian (توسيع البحث), pac bayesian (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
binary task » binary mask (توسيع البحث)
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Table 1_A comparative analysis of binary and multi-class classification machine learning algorithms to detect current frailty status using the English longitudinal study of ageing...
منشور في 2025"…</p>Conclusion<p>Machine learning algorithms show promise for the detection of current frailty status, particularly in binary classification. …"
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Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things
منشور في 2025"…In general, BRBPNN does not show any optimization adaption methods to determine the optimal parameter for appropriate detection. Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …"
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Confusion metrics using LR-HaPi algorithm.
منشور في 2024"…Nonetheless, the purview of propaganda detection transcends textual data alone. Deep learning algorithms like Artificial Neural Networks (ANN) offer the capability to manage multimodal data, incorporating text, images, audio, and video, thereby considering not only the content itself but also its presentation and contextual nuances during dissemination.…"
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Confusion metrics using MNB-HaPi algorithm.
منشور في 2024"…Nonetheless, the purview of propaganda detection transcends textual data alone. Deep learning algorithms like Artificial Neural Networks (ANN) offer the capability to manage multimodal data, incorporating text, images, audio, and video, thereby considering not only the content itself but also its presentation and contextual nuances during dissemination.…"
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Confusion metrics using DT-HaPi algorithm.
منشور في 2024"…Nonetheless, the purview of propaganda detection transcends textual data alone. Deep learning algorithms like Artificial Neural Networks (ANN) offer the capability to manage multimodal data, incorporating text, images, audio, and video, thereby considering not only the content itself but also its presentation and contextual nuances during dissemination.…"
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Confusion metrics using SVM-HaPi algorithm.
منشور في 2024"…Nonetheless, the purview of propaganda detection transcends textual data alone. Deep learning algorithms like Artificial Neural Networks (ANN) offer the capability to manage multimodal data, incorporating text, images, audio, and video, thereby considering not only the content itself but also its presentation and contextual nuances during dissemination.…"
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Algoritmo de detección de odio en español (Algorithm for detection of hate speech in Spanish)
منشور في 2024"…</li></ul><h2>Training Process</h2><h3>Pre-workout</h3><ul><li>Batch size: 16</li><li>Epochs: 5</li><li>Learning rate: 2e-5 with 10% warmup steps</li><li>Early stopping with patience=2</li></ul><h3>Fine-tuning</h3><ul><li>Batch size: 128</li><li>Epochs: 5</li><li>Learning rate: 2e-5 with 10% warmup steps</li><li>Early stopping with patience=2</li><li>Custom metrics:</li><li>Recall for non-hate class</li><li>Precision for hate class</li><li>F1-score (weighted)</li><li>AUC-PR</li><li>Recall at precision=0.9 (non-hate)</li><li>Precision at recall=0.9 (hate)</li></ul><h2>Evaluation Metrics</h2><p dir="ltr">The model is evaluated using:</p><ul><li>Macro recall, precision, and F1-score</li><li>One-vs-Rest AUC</li><li>Accuracy</li><li>Metrics by class</li><li>Confusion matrix</li></ul><h2>Requirements</h2><p dir="ltr">The following Python packages are required (see requirements.txt for the full list):</p><ul><li>TensorFlow</li><li>Transformers</li><li>scikit-learn</li><li>pandas</li><li>datasets</li><li>matplotlib</li><li>seaborn</li></ul><h2>Usage</h2><p dir="ltr">The model expects input data with the following specifications:</p><ol><li><b>Data Format</b>:</li></ol><ul><li>CSV file or Pandas DataFrame</li><li>Mandatory column name: <code>text</code> (type string)</li><li>Optional column name: <code>label</code> (type integer, 0 or 1) if available for evaluation</li></ul><ol><li><b>Text Preprocessing</b>:</li></ol><ul><li>Text will be automatically converted to lowercase during processing</li><li>Maximum length: 128 tokens (longer texts will be truncated)</li><li>Special characters, URLs, and emojis must remain in the text (the tokenizer handles these)</li></ul><ol><li><b>Label Encoding</b>:</li></ol><ul><li><code>0</code> = No hateful content (including neutral/positive content)</li><li>1 = Hate speech</li></ul><p dir="ltr">The process of creating this algorithm is explained in the technical report located at:Blanco-Valencia, X., De Gregorio-Vicente, O., Ruiz Iniesta, A., & Said-Hung, E. (2025). …"
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Related studies on IDS using deep learning.
منشور في 2024"…By focusing on datasets with this imbalance, we aim to develop and refine advanced algorithms and techniques, such as anomaly detection, cost-sensitive learning, and oversampling methods, to effectively handle such disparities. …"
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Melanoma Detection by Means of Multiple Instance Learning
منشور في 2021"…We present an application to melanoma detection of a multiple instance learning (MIL) approach, whose objective, in the binary case, is to discriminate between positive and negative sets of items. …"
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Image 1_From genetic data to kinship clarity: employing machine learning for detecting incestuous relations.jpeg
منشور في 2025"…Several machine learning algorithms and neural networks were tested for classification accuracy.…"
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