بدائل البحث:
based optimization » whale optimization (توسيع البحث)
from optimization » fox optimization (توسيع البحث), swarm optimization (توسيع البحث), codon optimization (توسيع البحث)
binary cases » binary values (توسيع البحث), binary labels (توسيع البحث), binary mask (توسيع البحث)
class based » classes based (توسيع البحث), cases based (توسيع البحث), charts based (توسيع البحث)
cases from » changes from (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
from optimization » fox optimization (توسيع البحث), swarm optimization (توسيع البحث), codon optimization (توسيع البحث)
binary cases » binary values (توسيع البحث), binary labels (توسيع البحث), binary mask (توسيع البحث)
class based » classes based (توسيع البحث), cases based (توسيع البحث), charts based (توسيع البحث)
cases from » changes from (توسيع البحث)
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Testing results for classifying AD, MCI and NC.
منشور في 2024"…<div><p>This study aims to develop an optimally performing convolutional neural network to classify Alzheimer’s disease into mild cognitive impairment, normal controls, or Alzheimer’s disease classes using a magnetic resonance imaging dataset. …"
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Summary of existing CNN models.
منشور في 2024"…<div><p>This study aims to develop an optimally performing convolutional neural network to classify Alzheimer’s disease into mild cognitive impairment, normal controls, or Alzheimer’s disease classes using a magnetic resonance imaging dataset. …"
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Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes
منشور في 2022"…Introduction: Increasingly, logistic regression methods for genetic association studies of binary phenotypes must be able to accommodate data sparsity, which arises from unbalanced case-control ratios and/or rare genetic variants. …"
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Analysis and design of algorithms for the manufacturing process of integrated circuits
منشور في 2023"…Additionally, the results obtained from our new ILP model indicate that our genetic algorithm results are very close to the optimal values.…"
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Programs to evaluate superoptimizer STOKE.
منشور في 2022"…We conclude from the experiments described in this paper that STOKE is able to fulfill that statement in some cases. …"
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Algoritmo de clasificación de expresiones de odio por tipos en español (Algorithm for classifying hate expressions by type in Spanish)
منشور في 2024"…</li></ul><p dir="ltr"><b>File Structure</b></p><p dir="ltr">The code generates and saves:</p><ul><li>Weights of the trained model (.h5)</li><li>Configured tokenizer</li><li>Training history in CSV</li><li>Requirements file</li></ul><p dir="ltr"><b>Important Notes</b></p><ul><li>The model excludes category 2 during training</li><li>Implements transfer learning from a pre-trained model for binary hate detection</li><li>Includes early stopping callbacks to prevent overfitting</li><li>Uses class weighting to handle category imbalances</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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Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat.
منشور في 2025"…The consistent accuracy of 70.28% does not represent a flaw in the SVM. algorithm, but rather the predictive performance ceiling of the feature itself, whose simplicity and class overlap limit the model's discriminatory ability. …"
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Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf
منشور في 2020"…The proposed multilabel approaches convert the original 8-class problem into a set of three binary problems to facilitate the use of the CSP algorithm. …"
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Processed dataset to train and test the WGAN-GP_IMOA_DA_Ensemble model
منشور في 2025"…This framework integrates a novel biologically inspired optimization algorithm, the Indian Millipede Optimization Algorithm (IMOA), for effective feature selection. …"
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Supplementary Material 8
منشور في 2025"…</li><li><b>XGboost: </b>An optimized gradient boosting algorithm that efficiently handles large genomic datasets, commonly used for high-accuracy predictions in <i>E. coli</i> classification.…"
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DataSheet_1_Exploring deep learning radiomics for classifying osteoporotic vertebral fractures in X-ray images.docx
منشور في 2024"…Utilizing the binary “One-vs-Rest” strategy, the model based on the RadImageNet dataset demonstrated superior efficacy in predicting Class 0, achieving an AUC of 0.969 and accuracy of 0.863. …"
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DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
منشور في 2024"…Regarding multiclass variables, accuracy remained consistent across classes, models, and NIR instruments (~0.63). However, the KNN model demonstrated slightly superior accuracy in classifying all cooking time classes, except for the CT4C variable (QST) in the NoCook and 25 min classes. …"
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Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
منشور في 2024"…Regarding multiclass variables, accuracy remained consistent across classes, models, and NIR instruments (~0.63). However, the KNN model demonstrated slightly superior accuracy in classifying all cooking time classes, except for the CT4C variable (QST) in the NoCook and 25 min classes. …"