يعرض 121 - 140 نتائج من 142 نتيجة بحث عن '(( binary based feature optimization algorithm ) OR ( binary risk based optimization algorithm ))', وقت الاستعلام: 0.59s تنقيح النتائج
  1. 121

    Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP حسب Xiaoyuan Wang (492534)

    منشور في 2022
    "…In this paper, a non-invasive and low-cost method of fatigue driving state identification based on genetic algorithm optimization of generalized regression neural network model is proposed. …"
  2. 122

    DataSheet_1_Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates.pdf حسب Marcel Dahms (9160118)

    منشور في 2022
    "…Improvement of the classification rate is expected with optimized model parameters and algorithms as well as with a larger spectral data base for training.…"
  3. 123
  4. 124

    Sample image for illustration. حسب Indhumathi S. (19173013)

    منشور في 2024
    "…This article introduces a Convex Based Feature Descriptor (CBFD) system designed to withstand rotation, lighting, and blur variations while remaining computationally efficient. …"
  5. 125

    Comparison analysis of computation time. حسب Indhumathi S. (19173013)

    منشور في 2024
    "…This article introduces a Convex Based Feature Descriptor (CBFD) system designed to withstand rotation, lighting, and blur variations while remaining computationally efficient. …"
  6. 126

    Process flow diagram of CBFD. حسب Indhumathi S. (19173013)

    منشور في 2024
    "…This article introduces a Convex Based Feature Descriptor (CBFD) system designed to withstand rotation, lighting, and blur variations while remaining computationally efficient. …"
  7. 127

    Precision recall curve. حسب Indhumathi S. (19173013)

    منشور في 2024
    "…This article introduces a Convex Based Feature Descriptor (CBFD) system designed to withstand rotation, lighting, and blur variations while remaining computationally efficient. …"
  8. 128

    Quadratic polynomial in 2D image plane. حسب Indhumathi S. (19173013)

    منشور في 2024
    "…This article introduces a Convex Based Feature Descriptor (CBFD) system designed to withstand rotation, lighting, and blur variations while remaining computationally efficient. …"
  9. 129

    Algoritmo de clasificación de expresiones de odio por tipos en español (Algorithm for classifying hate expressions by type in Spanish) حسب Daniel Pérez Palau (11097348)

    منشور في 2024
    "…</p><h2>Model Architecture</h2><p dir="ltr">The model is based on <code>pysentimiento/robertuito-base-uncased</code> with the following modifications:</p><ul><li>A dense classification layer was added over the base model</li><li>Uses input IDs and attention masks as inputs</li><li>Generates a multi-class classification with 5 hate categories</li></ul><h2>Dataset</h2><p dir="ltr"><b>HATEMEDIA Dataset</b>: Custom hate speech dataset with categorization by type:</p><ul><li><b>Labels</b>: 5 hate type categories (0-4)</li><li><b>Preprocessing</b>:</li><li>Null values ​​removed from text and labels</li><li>Reindexing and relabeling (original labels are adjusted by subtracting 1)</li><li>Exclusion of category 2 during training</li><li>Conversion of category 5 to category 2</li></ul><h2>Training Process</h2><h3>Configuration</h3><ul><li><b>Batch size</b>: 128</li><li><b>Epoches</b>: 5</li><li><b>Learning rate</b>: 2e-5 with 10% warmup steps</li><li><b>Early stopping</b> with patience=2</li><li><b>Class weights</b>: Balanced to handle class imbalance</li></ul><h3>Custom Metrics</h3><ul><li>Recall for specific classes (focus on class 2)</li><li>Precision for specific classes (focus on class 3)</li><li>F1-score (weighted)</li><li>AUC-PR</li><li>Recall at precision=0.6 (class 3)</li><li>Precision at recall=0.6 (class 2)</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>Per-class metrics</li><li>Confusion matrix</li><li>Full classification report</li></ul><h2>Technical Features</h2><h3>Data Preprocessing</h3><ul><li><b>Tokenization</b>: Maximum length of 128 tokens (truncation and padding)</li><li><b>Encoding of labels</b>: One-hot encoding for multi-class classification</li><li><b>Data split</b>: 80% training, 10% validation, 10% testing</li></ul><h3>Optimization</h3><ul><li><b>Optimizer</b>: Adam with linear warmup scheduling</li><li><b>Loss function</b>: Categorical Crossentropy (from_logits=True)</li><li><b>Imbalance handling</b>: Class weights computed automatically</li></ul><h2>Requirements</h2><p dir="ltr">The following Python packages are required:</p><ul><li>TensorFlow</li><li>Transformers</li><li>scikit-learn</li><li>pandas</li><li>datasets</li><li>matplotlib</li><li>seaborn</li><li>numpy</li></ul><h2>Usage</h2><ol><li><b>Data format</b>:</li></ol><ul><li>CSV file or Pandas DataFrame</li><li>Required column name: <code>text</code> (string type)</li><li>Required column name: Data type label (integer type, 0-4) - optional for evaluation</li></ul><ol><li><b>Text preprocessing</b>:</li></ol><ul><li>Automatic tokenization with a maximum length of 128 tokens</li><li>Long texts will be automatically truncated</li><li>Handling of special characters, URLs, and emojis included</li></ul><ol><li><b>Label encoding</b>:</li></ol><ul><li>The model classifies hate speech into 5 categories (0-4)</li><li><code>0</code>: Political hatred: Expressions directed against individuals or groups based on political orientation.…"
  10. 130

    Contextual Dynamic Pricing with Strategic Buyers حسب Pangpang Liu (18886419)

    منشور في 2024
    "…This underscores the rate optimality of our policy. Importantly, our policy is not a mere amalgamation of existing dynamic pricing policies and strategic behavior handling algorithms. …"
  11. 131

    Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf حسب Cecilia Lindig-León (7889777)

    منشور في 2020
    "…In this way, for each binary problem, the CSP algorithm produces features to determine if the specific body part is engaged in the task or not. …"
  12. 132

    Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield... حسب Uttam Khatri (12689072)

    منشور في 2022
    "…Finally, we implemented and compared the different feature selection algorithms to integrate the structural features, brain networks, and voxel features to optimize the diagnostic identifications of AD using support vector machine (SVM) classifiers. …"
  13. 133

    Supplementary Material 8 حسب Nishitha R Kumar (19750617)

    منشور في 2025
    "…</li><li><b>Linear support vector machine (Linear SVM):</b> This machine finds the optimal hyperplane to separate E. coli strains based on genomic features such as gene presence or sequence variations.…"
  14. 134

    Psoas muscle CT radiomics-based machine learning models to predict response to infliximab in patients with Crohn’s disease حسب Zhuoyan Chen (12193358)

    منشور في 2025
    "…<i>Z</i> score standardization and independent sample <i>t</i> test were applied to identify optimal predictive features, which were then utilized in seven ML algorithms for training and validation. …"
  15. 135

    Table_1_iRNA5hmC: The First Predictor to Identify RNA 5-Hydroxymethylcytosine Modifications Using Machine Learning.docx حسب Yuan Liu (88411)

    منشور في 2020
    "…In this predictor, we introduced a sequence-based feature algorithm consisting of two feature representations, (1) k-mer spectrum and (2) positional nucleotide binary vector, to capture the sequential characteristics of 5hmC sites. …"
  16. 136

    DataSheet_1_Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.docx حسب Yuhong Huang (115702)

    منشور في 2021
    "…We applied several feature selection strategies including the least absolute shrinkage and selection operator (LASSO), and recursive feature elimination (RFE), the maximum relevance minimum redundancy (mRMR), Boruta and Pearson correlation analysis, to select the most optimal features. …"
  17. 137

    Models and Dataset حسب M RN (9866504)

    منشور في 2025
    "…<p dir="ltr"><b>P3DE (Parameter-less Population Pyramid with Deep Ensemble):</b><br>P3DE is a hybrid feature selection framework that combines the Parameter-less Population Pyramid (P3) metaheuristic optimization algorithm with a deep ensemble of autoencoders. …"
  18. 138

    Processed dataset to train and test the WGAN-GP_IMOA_DA_Ensemble model حسب Ramya Chinnasamy (21633527)

    منشور في 2025
    "…This framework integrates a novel biologically inspired optimization algorithm, the Indian Millipede Optimization Algorithm (IMOA), for effective feature selection. …"
  19. 139

    DataSheet_1_Exploring deep learning radiomics for classifying osteoporotic vertebral fractures in X-ray images.docx حسب Jun Zhang (48506)

    منشور في 2024
    "…Logistic regression emerged as the optimal machine learning algorithm for both DLR models. …"
  20. 140

    DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx حسب Massaine Bandeira e Sousa (7866242)

    منشور في 2024
    "…Classification of genotypes was carried out using the K-nearest neighbor algorithm (KNN) and partial least squares (PLS) models. …"