Titlebook: Rough Sets; Theoretical Aspects Zdzisław Pawlak Book 1991 Springer Science+Business Media Dordrecht 1991 Equivalence.Pattern Recognition.a

出处

Machine Learning set approach, can be used as a theoretical basis for some problems in machine learning. In this section we are going to outline briefly some ideas showing how the concepts introduced so far can be used in this area. We do not pretend however to give full account for machine learning in the rough set perspective.

领带

Graphite

VALID

驾驶

Knowledge RepresentationThe issue of knowledge representation is of primary importance in current research in AI and variety of approaches can be found in this area (cf. Bobrow (1977), Bobrow et al. (1977), Brachmann et al.(1980), Davis et. al. (1982), Minski (1975), McDermott (1978), Newell (1982).

Antecedent

CAPE

从属

Data AnalysisIn this chapter we shall consider several examples of decision tables, which can be obtained as a result of observations or measurements, in contrast to decision tables considered in CHAPTER 8, which represented explicit knowledge of an agent or a group of agents.

DUCE

Dissimilarity AnalysisIn CHAPTERS 8 and 9 we confined our discussion of examples of Knowledge Representation Systems to those in which condition and decision attributes were distinguished i.e., to decision tables.

卡死偷电

Reduction of Knowledgen the knowledge considered. This problem arises in many practical applications and will be referred to as .. Its significance will be clearly seen in the second part of the book, where various applications are discussed.