Selective ensemble learning method for belief-rule-base classification system based on PAES
نویسندگان
چکیده
منابع مشابه
Online Fault Detection and Isolation Method Based on Belief Rule Base for Industrial Gas Turbines
Real time and accurate fault detection has attracted an increasing attention with a growing demand for higher operational efficiency and safety of industrial gas turbines as complex engineering systems. Current methods based on condition monitoring data have drawbacks in using both expert knowledge and quantitative information for detecting faults. On account of this reason, this paper proposes...
متن کاملFuzzy Rule Base System for Software Classification
Given the central role that software development plays in the delivery and application of information technology, managers have been focusing on process improvement in the software development area. This improvement has increased the demand for software measures, or metrics to manage the process. This metrics provide a quantitative basis for the development and validation of models during the s...
متن کاملRule Learning based on Neural Network Ensemble
Neural network ensemble can significantly improve the generalization ability of neural network based systems. In this paper, a novel rule learning algorithm is proposed, where neural network ensemble acts as a front-end process that generates data for the learning of rules. Experimental results show that the proposed algorithm can generate rules with strong generalization ability.
متن کاملEnsemble Relational Learning based on Selective Propositionalization
Dealing with structured data needs the use of expressive representation formalisms that, however, puts the problem to deal with the computational complexity of the machine learning process. Furthermore, real world domains require tools able to manage their typical uncertainty. Many statistical relational learning approaches try to deal with these problems by combining the construction of releva...
متن کاملA Novel Selective Ensemble Classification of Microarray Data Based on Teaching-Learning-Based Optimization
Aiming at the characteristics of high dimension and small samples in microarray data, this paper proposes a selective ensemble method to classify microarray data. Firstly, kruskal-wallis test is used to filter irrelevant genes with classification task and to obtain a set of genes, and then a reduced training set is produced from original training set according to gene subset obtained. Secondly,...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Big Data Mining and Analytics
سال: 2019
ISSN: 2096-0654
DOI: 10.26599/bdma.2019.9020008