Titlebook: ;

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https://doi.org/10.1007/978-3-031-41104-5ation between continuous features and binary class labels to facilitate classification modeling. A data visualization analysis framework is developed using weight of evidence (WOE), where a semi-supervised approach is proposed to discretize the continuous features for WOE computation targeting on th

SHOCK

https://doi.org/10.1007/978-3-319-91890-7xt length leads to higher training costs of algorithms. It allows us to find that the common text classification algorithm models have shown significant influence on the standard English dataset and Reddit mental illness dataset. The length of text or a string, especially for controlling the maximum

Vertebra

失眠症

沉思的鱼

Green, Pervasive, and Cloud Computing – GPC 2020 Workshops978-981-33-4532-4Series ISSN 1865-0929 Series E-ISSN 1865-0937

破布

Martin Eastwoodal class as a form of stratification (and in particular on how ‘the working class’ has been conceived of and represented); through approaches which distinguished between ‘the economic’ and ‘the cultural’ (with the latter seen as critical in the analysis of gendered and racialised inequalities); the

contradict

incite

Internet of Things-Aware Process Modeling: Integrating IoT Devices as Business Process Resourcesstigation of such features very often has a bearing on practical problems of oil prospecting, the location of water-bearing strata, mineral exploration, highways construction and civil engineering. Often, the application of physics, in combination with geological information, is the only satisfactory way towards a solution of these problems.

Confess

Glycogen

Neutrosophic Soft Rough Graphs,Neutrosophic soft rough set model is a hybrid model by combining neutrosophic soft sets with rough sets. We apply neutrosophic soft rough sets to graphs. We present the concept of neutrosophic soft rough graphs and describe different methods of their construction. We develop an efficient algorithm of our method to solve decision-making problems.