Titlebook: Rough Set and Knowledge Technology; 6th International Co JingTao Yao,Sheela Ramanna,Zbigniew Suraj Conference proceedings 2011 Springer-Ver

Kindle

能量守恒

amplitude

cloture

Rule-Based Estimation of Attribute Relevancebutes. To this end, we are using Bayesian confirmation measure. The estimation is based on analysis of rule classifiers in classification tests. The attribute relevance measure increases when more rules involving this attribute suggest a correct decision, or when more rules that do not involve this

半導(dǎo)體

GEST

HEPA-filter

Optimal Sub-Reducts with Test Cost Constrainthe data. In many applications, there is a test cost constraint due to limited money, time, or other resources. It is necessary to deliberately choose a set of tests to preserve more useful information for classification. To cope with this issue, we define optimal sub-reducts with test cost constrain

originality

An Efficient Fuzzy-Rough Attribute Reduction Approachal values. However, its time-consumption is very intolerable to analyze data sets with large scale and high dimensionality. In this paper, we propose a strategy to improve a heuristic process of fuzzy-rough feature selection. Experiments show that this modified algorithm is much faster than its orig

Mets552

A Novel Attribute Reduction Approach Based on the Object Oriented Concept Latticeased on the object oriented concept lattice are investigated. We first introduce the notions of context matrix and the operations of corresponding column vectors. Then present some judgment theorems for attribute reduction in formal contexts. Based on the judgment theorems, we propose an attribute r

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