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custom algorithm » control algorithm (Expand Search), auction algorithm (Expand Search), cosine algorithm (Expand Search)
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custom algorithm » control algorithm (Expand Search), auction algorithm (Expand Search), cosine algorithm (Expand Search)
coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
rf algorithm » rd algorithm (Expand Search), _ algorithms (Expand Search)
complement » implement (Expand Search), complementary (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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Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms
Published 2022“…Extracted vegetation indices were evaluated on three ML algorithms, namely, random forest (RF), k-nearest neighbour (K-NN), and k dimensional-tree (KD-Tree). …”
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A novel hybrid methodology for fault diagnosis of wind energy conversion systems
Published 2023“…Therefore, a hybrid feature selection based diagnosis technique, that can preserve the advantages of wrapper and filter algorithms as well as RF model, is proposed. In the first phase, the neighborhood component analysis (NCA) filter algorithm is used to reduce and select only the pertinent features from the original raw data. …”
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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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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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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). …”