Probabilistic Approximation under Incomplete Information Systems
نویسندگان
چکیده
By applying the probability estimation of the unavailable attributes derived from the available attributes to the neighborhood system, the suited degree of each neighbor to a given object is depicted. Therefore, the neighborhood space with guaranteed suited precision is obtained. We show how to shrink the rule search space via VPRS model for this space, and also, we will prove the incredibility degree of decision class is guaranteed by the two-layer thresholds.
منابع مشابه
Extension of Cube Attack with Probabilistic Equations and its Application on Cryptanalysis of KATAN Cipher
Cube Attack is a successful case of Algebraic Attack. Cube Attack consists of two phases, linear equation extraction and solving the extracted equation system. Due to the high complexity of equation extraction phase in finding linear equations, we can extract nonlinear ones that could be approximated to linear equations with high probability. The probabilistic equations could be considered as l...
متن کاملA Rough Set Model Based on Probabilistic Similarity Measure for Incomplete Decision Tables
Rough set models in incomplete decision tables have been discussed so far. Numerous approaches to deal with missing values in incomplete information systems have been proposed. In this paper, assuming that the domain of attribute values is defined, we apply the probability of values appearing in data tables in order to measure the self-information of similarity. This is defined as the uncertain...
متن کاملMulti-granulation fuzzy probabilistic rough sets and their corresponding three-way decisions over two universes
This article introduces a general framework of multi-granulation fuzzy probabilistic roughsets (MG-FPRSs) models in multi-granulation fuzzy probabilistic approximation space over twouniverses. Four types of MG-FPRSs are established, by the four different conditional probabilitiesof fuzzy event. For different constraints on parameters, we obtain four kinds of each type MG-FPRSs...
متن کاملPositive Approximation and Rule Extracting in Incomplete Information Systems
Set approximation is a kernel concept in rough set theory. In this paper, by introducing a notion of granulation order, positive approximation of a target set under a granulation order is defined in an incomplete information system and its some useful properties are investigated. Unlike classical rough set theory, this approximation deals with how to describe the structure of a rough set in inc...
متن کاملAbout Planning under Uncertainty in Dynamic Systems Exploiting Probabilistic Information
To sUIvive in a real world environment, a reasoning agent has to be equipped with several capabilities ;.n order tc deal with incomplete information about its target domain. One aspect of the incomplete information is the uncertainty about the effects of actions and events . Although the concrete outcome of an action or event cannot be predicted, often their relative likelihood can be quantifie...
متن کامل