13 results for “Imputation”

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Research ArticleOpen accessIn the abstractMissing Values Treatment and Feature Reduction Analysis to Enhance ClassificationD. Muralidharan, K. Renuka, Mulagala Jaswant et al.Datasets may have large number of features which makes it hard and time consuming to classify. Additionally, they may have irrelevant and noise features too with missing values. The missing values should be treated in a proper way so that the classifier accuracy can be improved. There is also a need to reduce features and select only the features necessary … …Journal of Computer Science, Vol. 16, Issue 2 · 20 Feb 2020 · 8,114 accessesView PDF Cite

Research ArticleOpen accessIn the abstractStructure of a Photovoltaic Electric LocomotiveFlorian Ion Tiberiu PetrescuThe paper proposes to start studies at the global level for the implementation of photovoltaic electric locomotives. The question the author asks is why such trains have not been implemented so far, is there no interest in such a thing? This may avoid the current rush to implement 5G technologies in an already extremely dangerous form for humanity, the rush … …American Journal of Engineering and Applied Sciences, Vol. 12, Issue 4 · 16 Nov 2019 · 7,191 accessesView PDF Cite

Research ArticleOpen accessIn the abstractGeneral Linear Models in a Missing Outcome Environment of Clinical Trials Incorporating with Splines for Time-Invariant Continuous AdjustmentMinjeong Park, Dejian Lai, Xianglin L. Du et al.Missing data is a common occurrence in longitudinal studies of health care research. Although many studies have shown the potential usefulness of current missing analyses, e.g., (1) Complete Case (CC) analysis; (2) imputation methods such as Last Observation Carried Forward (LOCF), multiple imputations, Expectation-Maximization algorithm approach; and (3) methods using all available data such as linear mixed model and generalized … …Current Research in Biostatistics, Vol. 5, Issue 1 · 18 Aug 2015 · 7,401 accessesView PDF Cite