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Discriminable Multi-Label Attribute Selection for Pre-Course Student Performance Prediction [PDF]
Entropy, 2021 The university curriculum is a systematic and organic study complex with some immediate associated steps; the initial learning of each semester’s course is crucial, and significantly impacts the learning process of subsequent courses and further studies.
Jie Yang +3 more
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IEEE Access, 2021 Attribute selection is the process of selecting relevant attributes being used in model construction to enhance model accuracy. For general medical oriented classification applications, classical attribute selection methods principally select common ...
Supansa Chaising +2 more
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Attribute Selection via Maximizing Independent-and-Effective Classification Information Ratio [PDF]
Jisuanji kexue yu tansuo, 2022 Attribute selection in rough set theory has wide practical application values. Most existing attribute selection approaches neglect the relationship among the classification information and redundant information brought by the candidate attribute, and ...
LIU Ye, DAI Jianhua, CHEN Jiaolong
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Machine Learning-Based Energy Consumption Estimation of Wastewater Treatment Plants in Greece
Energies, 2023 Amidst a global discourse on energy resources, it is imperative to provide decision makers with a comprehensive overview of energy consumption (EC) associated with various projects, particularly wastewater treatment plants (WWTPs).
Panagiotis Karadimos +1 more
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Attribute Selection Using Contranominal Scales [PDF]
, 2021 Formal Concept Analysis (FCA) allows to analyze binary data by deriving concepts and ordering them in lattices. One of the main goals of FCA is to enable humans to comprehend the information that is encapsulated in the data; however, the large size of concept lattices is a limiting factor for the feasibility of understanding the underlying structural ...
Dominik Dürrschnabel +2 more
openaire +2 more sources
Clustering in Wineinformatics with Attribute Selection to Increase Uniqueness of Clusters
Fermentation, 2021 Wineinformatics is a new data science research area that focuses on large amounts of wine-related data. Most of the current Wineinformatics researches are focused on supervised learning to predict the wine quality, price, region and weather.
Jared McCune, Alex Riley, Bernard Chen
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MLP-Based Attribute Selection Method for Handwritten Signatures Authentication [PDF]
ITM Web of Conferences, 2023 Finding the most unique traits that have strong discrimination capacities to be used for confirmation, in particular with reference to the substantial variation that’s intrinsic in real signatures, is among the main difficulties in developing an ...
Wani Hemant A. +2 more
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Dwell Time Estimation of Import Containers as an Ordinal Regression Problem
Applied Sciences, 2021 The optimal stacking of import containers in a terminal reduces the reshuffles during the unloading operations. Knowing the departure date of each container is critical for optimal stacking.
Laidy De Armas Jacomino +5 more
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Frontiers in Psychology, 2021 Maximum deviation global discrimination index (MDGDI) is a new item selection method for cognitive diagnostic computerized adaptive testing that allows for attribute coverage balance. We developed the maximum limitation global discrimination index (MLGDI)
Junjie Li +3 more
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Objects2action: Classifying and localizing actions without any video example [PDF]
, 2015 The goal of this paper is to recognize actions in video without the need for examples. Different from traditional zero-shot approaches we do not demand the design and specification of attribute classifiers and class-to-attribute mappings to allow for ...
Jain, Mihir +3 more
core +17 more sources