Rule Induction: Combining Rough Set and Statistical Approaches
نویسنده
چکیده
In this paper we propose the hybridisation of the rough set concepts and statistical learning theory. We introduce new estimators for rule accuracy and coverage, which base on the assumptions of the statistical learning theory. Then we construct classifier which uses these estimators for rule induction. These estimators allow us to select rules describing statistically significant dependencies in data. We test our classifier on benchmark datasets and show its applications for KDD.
منابع مشابه
A hybrid filter-based feature selection method via hesitant fuzzy and rough sets concepts
High dimensional microarray datasets are difficult to classify since they have many features with small number ofinstances and imbalanced distribution of classes. This paper proposes a filter-based feature selection method to improvethe classification performance of microarray datasets by selecting the significant features. Combining the concepts ofrough sets, weighted rough set, fuzzy rough se...
متن کاملApplication 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 کاملVC-DomLEM: Rule induction algorithm for variable consistency rough set approaches
We present a general rule induction algorithm based on sequential covering, suitable for variable consistency rough set approaches. This algorithm, called VC-DomLEM, can be used for both ordered and non-ordered data. In the case of ordered data, the rough set model employs dominance relation, and in the case of non-ordered data, it employs indiscernibility relation. VC-DomLEM generates a minima...
متن کاملCombining rough sets and rule based classifiers for handling imbalanced data
The paper presents two rough sets based filtering approaches combined with rule based classifiers suited for handling imbalanced data sets, i.e., data sets where the minority class of primary importance is under-represented in comparison to the majority classes. We introduced two techniques to detect and process inconsistent majority cases in the boundary between the minority and majority class...
متن کاملSeveral Considerations on Statistical Test Rule Induction Method
STRIM (Statistical Test Rule Induction Method) has been proposed as a method to effectively induct if-then rules from the decision table. The method was studied independently of the conventional rough sets methods. This paper summarizes the basic concept of STRIM, considers the relationship between STRIM and conventional methods, especially VPRS (Variable Precision Rough Set), and shows that ST...
متن کاملذخیره 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 2008