Sentence examples for decision inference from inspiring English sources

Then, the users can use the decision inference module to derive plausible alternatives while referring to collected and classified information.

A validity argument of decision inference was evidenced by basic-level students' score gain on an achievement test and their positive class evaluations.

This study presents a web-based group decision support system that considers the decision making process as a whole, including idea generation and sharing, planning, discussion, decision inference, and evaluation.

Internal and external information is managed and can be retrieved efficiently by using structured searching functions; and (ii) a decision inference module in which decisions can be made either by a rule-based reasoning model for a certain situation or by a Bayesian network-based reasoning model for a probabilistic situation.

An overview of classifiers that are used in CDSS is introduced in Section 2. The experiment to be conducted is described in details in Section 3. The second phase of rt-CDSS namely the decision inference is given in Section 4. Section 5 concludes the paper.

Smets and Kennes have claimed that the transferable belief model, a decision and inference procedure based upon the Dempster-Shafer formalism, never exposes the believer to a kind of betting conundrum known as a "Dutch book".

As a higher-layer cognitive process, problem solving interacts with many other cognitive processes such as abstraction, searching, learning, decision making, inference, analysis, and synthesis on the basis of internal knowledge representation by the object attribute-relation (object attribute-relation

Instead, subtle data characteristics would have a greater chance of participating in the decision rule inference.

The security refers to the classifier can unbiasedly recognize each label type by avoiding possible biases in the classifier 's decision function inference.

Alternatively, the DCA-SVM 's feature space contains 'de-noised' true signals with the subtle data characteristics, which avoids the global data characteristics favored decision rule inference because the subtle data characteristics are also invited in SVM hyperplane construction besides the global data characteristics.

Lewis et al. [ 23] proposed this approach mimicking pruning performed in decision tree inferences, which is essential to reduce over-fitting [ 31].