In some statistical process control applications, the combination of both variable and attribute quality characteristics which are correlated represents the quality of the product or the process. In such processes, identification the time of manifesting the out-of-control states can help the quality engineers to eliminate the assignable causes through proper corrective actions. In this paper, f...

Many types of tumors exhibit characteristic chromosomal losses or gains, as well as local amplifications and deletions. Within any given tumor type, sample specific amplifications and deletions are also observed. Typically, a region that is aberrant in more tumors, or whose copy number change is stronger, would be considered as a more promising candidate to be biologically relevant to cancer. W...

P-sets (P stands for Packet), a set pair with dynamic and law characteristics, are made up of an internal outer P-set, which is obtained by introducing characteristics into the Cantor improving set. The concepts αF-sub-information, αF¯-sub-information, (αF,αF¯)-sub-information presented in this paper based on P-sets, it then suggested that relationship between generation sub-information its att...

Rough set theory is used for dealing with uncertainty in the hidden pattern of data. This paper outlines concepts of the rough set theory for lower and upper approximations, reduction of attributes and decision rules. It assumes that the information about the real world is given in the form of an information table which represents input data, gathered from any domain, such as, medicine, finance...

Dominance-based Rough Sets Approach (DRSA) is a generalized model of the classical Rough Sets Theory (RST) which may handle information with preference-ordered attribute domain. The attribute set in the information system may evolve over time. Approximations of DRSA used to induce decision rules need updating for knowledge discovery and other related tasks. We firstly introduce a kind of domina...

to identify important attributes/factors that contribute to grain and biological yields of wheat, 9912 sets of diverse data from field studies were extracted, and supervised attribute-weighting models were employed. results showed that when biological yield was the output, grain yield, nitrogen applied, rainfall, irrigation regime, and organic content were the most important factors/attributes,...

The database model presented in this paper is suitable for application in which queries may require non-crisp references to certain attributes. The data item (attribute) values may be crisp or fuzzy. For instance, such adjectives as 'high' or 'normal' may be attribute values for the attribute blood pressure. A disease or a condition can be described by a number of symptoms which may be crisp al...

In this paper, we examine Decision Graphs, a generalization of decision trees. We present an inference scheme to construct decision graphs using the Minimum Message Length Principle. Empirical tests demonstrate that this scheme compares favourably with other decision tree inference schemes. This work provides a metric for comparing the relative merit of the decision tree and decision graph form...