Results 41 to 50 of about 82,468 (189)
Multi-TGDR: a regularization method for multi-class classification in microarray experiments [PDF]
, 2013 Background With microarray technology becoming mature and popular, the selection and use of a small number of relevant genes for accurate classification of samples is a hot topic in the circles of biostatistics and bioinformatics.
Suárez-Fariñas, Mayte, Tian, Suyan
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Ciência Rural: Fruit bagging is an efficient mechanical control technique used in fruit growing. However, to date, few studies have evaluated the efficacy of bagging in the cultivation of vegetables, including tomato crops. The objective of this study was to evaluate
Rosenya Michely Cintra Filgueiras +5 more
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Entropy, 2018 Recently, the Entropy Ensemble Filter (EEF) method was proposed to mitigate the computational cost of the Bootstrap AGGregatING (bagging) method. This method uses the most informative training data sets in the model ensemble rather than all ensemble ...
Hossein Foroozand +2 more
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Bagging of bunches and protected production in ‘Niagara Rosada’ vineyard
Pesquisa Agropecuária Gaúcha, 2021 Vineyards of ‘Niagara Rosada’ have shown great productive potential. However, the grape production has been affected by factors related to climate adversities.
Inês Thomaz Guérios +2 more
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Ensembles of probability estimation trees for customer churn prediction [PDF]
, 2010 Customer churn prediction is one of the most, important elements tents of a company's Customer Relationship Management, (CRM) strategy In tins study, two strategies are investigated to increase the lift. performance of ensemble classification models, i.e
A. Lemmens +20 more
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An Improved-Bagging Model for Water Chemical Oxygen Demand Measurements Using UV-Vis Spectroscopy
IEEE Access, 2021 The ultraviolet-visible (UV-Vis) spectroscopy measurement method of Chemical Oxygen Demand (COD) in water is a simple physical method that can measure water without secondary pollution from chemical reagents.
Jingwei Li +3 more
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Applied SciencesIn the field of ensemble learning, bagging and stacking are two widely used ensemble strategies. Bagging enhances model robustness through repeated sampling and weighted averaging of homogeneous classifiers, while stacking improves classification ...
Ruinan Qiu +3 more
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Asymmetric bagging and random subspace for support vector machines-based relevance feedback in image retrieval [PDF]
, 2006 Relevance feedback schemes based on support vector machines (SVM) have been widely used in content-based image retrieval (CBIR). However, the performance of SVM-based relevance feedback is often poor when the number of labeled positive feedback samples ...
Li, Xuelong, Tang, X., Tao, D., Wu, X.
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Optimization of Signal Significance by Bagging Decision Trees [PDF]
, 2005 An algorithm for optimization of signal significance or any other classification figure of merit suited for analysis of high energy physics (HEP) data is described.
Narsky, I.
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Comparing Different Machine Learning Techniques in Predicting Diabetes on Early Stage
Engineering ProceedingsOne of the diseases that is constantly spreading and is estimated to cause a significant number of deaths worldwide is diabetes mellitus. It is determined by the quantity of a blood sugar molecule made from glucose.
Shweta Yadu +2 more
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