Some Relationships between Decision Trees and Decision Rule Systems

نویسنده

  • Mikhail Ju. Moshkov
چکیده

Relationships between parameters of a decision rule system and the minimal depth of a decision tree which solves the problem of the search of all realizable rules from the system are considered. Unim-provable upper and close to unimprovable lower bounds on the minimal depth of a decision tree are obtained.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

USING DISTRIBUTION OF DATA TO ENHANCE PERFORMANCE OF FUZZY CLASSIFICATION SYSTEMS

This paper considers the automatic design of fuzzy rule-basedclassification systems based on labeled data. The classification performance andinterpretability are of major importance in these systems. In this paper, weutilize the distribution of training patterns in decision subspace of each fuzzyrule to improve its initially assigned certainty grade (i.e. rule weight). Ourapproach uses a punish...

متن کامل

A New Algorithm for Optimization of Fuzzy Decision Tree in Data Mining

Decision-tree algorithms provide one of the most popular methodologies for symbolic knowledge acquisition. The resulting knowledge, a symbolic decision tree along with a simple inference mechanism, has been praised for comprehensibility. The most comprehensible decision trees have been designed for perfect symbolic data. Classical crisp decision trees (DT) are widely applied to classification t...

متن کامل

Application of Rough Set Theory in Data Mining for Decision Support Systems (DSSs)

Decision support systems (DSSs) are prevalent information systems for decision making in many competitive business environments. In a DSS, decision making process is intimately related to some factors which determine the quality of information systems and their related products. Traditional approaches to data analysis usually cannot be implemented in sophisticated Companies, where managers ne...

متن کامل

Knowledge Extraction from the Neural ‘Black Box’ in Ecological Monitoring

Phytoplankton biomass within the Saginaw Bay ecosystem (Lake Huron, Michigan, USA) was characterized as a function of select physical/chemical indicators. The complexity and variability of ecological systems typically make it difficult to model the influences of anthropogenic stressors and/or natural disturbances. Here, Artificial Neural Networks (ANNs) were developed to model chlorophyll a con...

متن کامل

Abductive Reasoning in Environmental Decision Support Systems

Decision trees and rule-based system including variants based on propositional and fuzzy logic have been the method of choice in many applications of environmental decision support systems. Reasons are the ease of use, the capability of representing uncertainty, and the fast computation of results at runtime when using decision trees or other similar means for knowledge representation. Unfortun...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1998