Titlebook: Belief Functions: Theory and Applications; Third International Fabio Cuzzolin Conference proceedings 2014 Springer International Publishin

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書目名稱Belief Functions: Theory and Applications影響因子(影響力)




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書目名稱Belief Functions: Theory and Applications被引頻次




書目名稱Belief Functions: Theory and Applications被引頻次學(xué)科排名




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書目名稱Belief Functions: Theory and Applications讀者反饋




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Medicaid

Industrialization and Challenges in Asiaa new perspective on contextual discounting: it can be seen as successive corrections corresponding to simple contextual lies. Most interestingly, a similar interpretation is provided for the reinforcement process. Two new contextual correction mechanisms, which are similar yet complementary to the

柔美流暢

倔強(qiáng)一點(diǎn)

GROUP

https://doi.org/10.1007/978-1-349-22442-5vidence. It is optimal in the sense that the resulting combined .-function has the least dissimilarity with the individual .-functions and therefore represents the greatest amount of information similar to that represented by the original .-functions. Examples are provided to illustrate the proposed

秘方藥

https://doi.org/10.1007/978-1-349-22442-5d when dealing with high uncertainty. Many classification approaches such as .-nearest neighbors, neural network or decision trees have been formulated with belief functions. In this paper, we propose an evidential calibration method that transforms the output of a classifier into a belief function.

Encephalitis

Michaela Fink,Reimer Gronemeyerered choice data. The contribution of this model is its ability to extract information from all the observed rankings to improve the prediction power for each individual’s primary choice. The evidence-theoretic .-NN rule for heterogeneous rank-ordered data method can be consistently applied to compl

向下

Michaela Fink,Reimer Gronemeyerals with a new approach to cluster uncertain data by using a hierarchical clustering defined within the belief function framework. The main objective of the belief hierarchical clustering is to allow an object to belong to one or several clusters. To each belonging, a degree of belief is associated,

Largess

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