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coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
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lr algorithm » rd algorithm (Expand Search), deer algorithm (Expand Search), _ algorithms (Expand Search)
coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
swarm algorithm » search algorithm (Expand Search)
lr algorithm » rd algorithm (Expand Search), deer algorithm (Expand Search), _ algorithms (Expand Search)
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CNN and HEVC Video Coding Features for Static Video Summarization
Published 2022Get full text
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Automatic Video Summarization Using HEVC and CNN Features
Published 2022Get full text
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Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms
Published 2022“…When comparing the actual and anticipated ground loss, the SVR performed best (R<sup>2</sup> = 0.79–0.93) as compared to the other two algorithms i.e., LR (R<sup>2</sup> = 0.73 to 0.92), and RF (R<sup>2</sup> = 0.53 to 0.89) for the three fields. …”
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Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn...
Published 2020“…A special consideration was given to data pre-processing and dimensionality reduction such Chi Squared (CS) and Recursive Feature Elimination (RFE) to improve progressively the proposed models performance. LR with the reduced feature set using the intersection between CS and RFE proved to be the best model among the tested algorithms. …”
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Sentiment Analysis of the Emirati Dialect text using Ensemble Stacking Deep Learning Models
Published 2023“…For the basic machine learning algorithms, LR, NB, SVM, RF, DT, MLP, AdaBoost, GBoost, and an ensemble model of machine learning classifiers were used. …”
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Oversampling techniques for imbalanced data in regression
Published 2024“…For tabular data, we also present the Auto-Inflater neural network, utilizing an exponential loss function for Autoencoders. …”
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Developing an online hate classifier for multiple social media platforms
Published 2020“…We then experiment with several classification algorithms (Logistic Regression, Naïve Bayes, Support Vector Machines, XGBoost, and Neural Networks) and feature representations (Bag-of-Words, TF-IDF, Word2Vec, BERT, and their combination). …”