Results 11 to 20 of about 129,844 (264)
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
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Future Internet, 2022 This paper addresses the regression modeling of local environmental pollution levels for electric power industry needs, which is fundamental for the proper design and maintenance of high-voltage transmission lines and insulators in order to prevent ...
Peter Krammer +7 more
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Attribute Selecting in Tree-Augmented Naive Bayes by Cross Validation Risk Minimization
Mathematics, 2021 As an important improvement to naive Bayes, Tree-Augmented Naive Bayes (TAN) exhibits excellent classification performance and efficiency since it allows that every attribute depends on at most one other attribute in addition to the class variable ...
Shenglei Chen +2 more
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Optimal Granularity Selection and Attribute Reduction in Meso-granularity Space [PDF]
Jisuanji kexue, 2023 The conventional formal concept analysis adopts a meso-granularity formal context to meet the requirements of cross-layer granulation of data.However,it does not effectively combine the search for optimal granularity with attribute reduction,nor does it ...
LI Teng, LI Deyu, ZHAI Yanhui, ZHANG Shaoxia
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Improving the accuracy of classification algorithms for inductive learning rules using wrapper methods [PDF]
Tehnika, 2015 In this paper we investigate the problem of the accuracy of classifier using wrapper methods. For the purposes of classification is used a large number of algorithms: IBK, Naïve Bayes, SVM, J48 decision tree and RBF networks.
Novaković Jasmina Đ.
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Attribute selection in multivariate microaggregation [PDF]
Proceedings of the 2008 international workshop on Privacy and anonymity in information society, 2008 Microaggregation is one of the most employed microdata protection methods. The idea is to build clusters of at least k original records, and then replace them with the centroid of the cluster. When the number of attributes of the dataset is large, a common practice is to split the dataset into smaller blocks of attributes.
Jordi Nin, Javier Herranz, Vicenç Torra
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Applied Sciences, 2023 Selection of a suitable additive manufacturing (AM) machine to manufacture a specific product is one of the important tasks in design for AM. So far, many selection approaches based on multi-attribute decision making have been proposed within academia ...
Meifa Huang +4 more
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Attribute selection strategies for attribute-oriented generalization [PDF]
, 1996 We describe and compare attribute-selection strategies for attribute-oriented generalization (AOG). AOG summarizes the information in a relational database by repeatedly replacing specific attribute values with more general concepts. Several strategies for selecting the next attribute to generalize have been suggested in the literature, but their ...
Brock Barber, Howard J. Hamilton
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Detection of interdependences in attribute selection [PDF]
, 1998 220
Javier Lorenzo 0001 +2 more
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Polish Maritime Research, 2017 At present, in the fault diagnosis database of submarine optical fiber network, the attribute selection of large data is completed by detecting the attributes of the data, the accuracy of large data attribute selection cannot be guaranteed. In this paper,
Chen Ganlang
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