Results 201 to 210 of about 23,894,114 (248)

Interpretability Assessment of Fuzzy Rule-Based Classifiers

2009
Interpretability is one of the most important driving forces for the adoption of fuzzy rule-based classifiers. However, it is not given for granted, especially when fuzzy models are acquired from data. Therefore, evaluation of interpretability should be regarded as a major research topic.
Corrado Mencar, Ciro Castiello, Anna Maria Fanelli   +2 more
openaire   +3 more sources

Classifying Categorical Data by Rule-Based Neighbors

2011 IEEE 11th International Conference on Data Mining, 2011
A new learning algorithm for categorical data, named CRN (Classification by Rule-based Neighbors) is proposed in this paper. CRN is a nonmetric and parameter-free classifier, and can be regarded as a hybrid of rule induction and instance-based learning.
Jiabing Wang, Pei Zhang, Guihua Wen, Jia Wei   +3 more
openaire   +1 more source

The Science of Rule-based Classifiers

2019 9th International Conference on Cloud Computing, Data Science & Engineering (Confluence), 2019
The exponential rise in the amount of data has fueled various facets in data science and data engineering. Classification is a supervised machine learning task that underlies several diagnosis systems and rule-based decision support systems. The efficiency of a rule-based classifier depends on factors such as quality of the rules in the ruleset, rule ...
openaire   +1 more source

Nondeterministic Decision Rules in Rule-Based Classifier

2014
In the paper is discussed the truncated nondeterministic rules and their role in an evaluation of classification model. The nondeterministic rules are created as the result of shorting deterministic rules in accordance with the principle of minimum description length (MDL).
Piotr Paszek, Barbara Marszal-Paszek
openaire   +1 more source

Evolving Fuzzy Rule-based Classifiers

2007 IEEE Symposium on Computational Intelligence in Image and Signal Processing, 2007
A novel approach to on-line classification based on fuzzy rules with an open/evolving structure is introduced in this paper. This classifier can start `from scratch', learning and adapting to the new data samples or from an initial rule-based classifier that can be updated based on the new information contained in the new samples.
Plamen Angelov, Xiaowei Zhou, Frank Klawonn   +2 more
openaire   +1 more source

Evolution of Fuzzy Rule Based Classifiers

2004
The paper presents an evolutionary approach for generating fuzzy rule based classifier. First, a classification problem is divided into several two-class problems following a fuzzy unordered class binarization scheme; next, a fuzzy rule is evolved (not only the condition but the fuzzy sets are evolved (tuned) too) for each two-class problem using a ...
openaire   +2 more sources

A Framework for Designing a Fuzzy Rule-Based Classifier

2009
This paper is concerned with a general framework for designing a fuzzy rule-based classifier. Structure and parameters of the classifier are evolved through a two-stage genetic search. The classifier structure is constrained by a tree created using the evolving SOM tree algorithm.
Jonas Guzaitis, Antanas Verikas, Adas Gelzinis, Marija Bacauskiene   +3 more
openaire   +1 more source

Parallel Implementation of a Fuzzy Rule Based Classifier

2005
This works presents an implementation of a fuzzy rule based classifier where each single variable fuzzy rule based classifier (or a set of them) is assigned to a different processor in a parallel architecture. Partial conclusions are synchronized and processed by a master processor.
Alexandre G. Evsukoff, Myrian C. A. Costa, Nelson F. F. Ebecken   +2 more
openaire   +2 more sources

A combined statistical and rule-based classifier

Images of the Twenty-First Century. Proceedings of the Annual International Engineering in Medicine and Biology Society, 2003
Summary form only given. A combined statistical and rule-based classifier is presented. It has been tested by classifying cervical cells. The statistical classifier is used to set up classification boundaries, and the expert knowledge in the rule-based classifier is used to monitor the overall situation and modify the classification boundaries ...
D. Tien, P. Nickolls
openaire   +1 more source

From Ensemble of Fuzzy Classifiers to Single Fuzzy Rule Base Classifier

2008
Neuro-fuzzy systems show very good performance and the knowledge comprised within their structure is easily interpretable. To further improve their accuracy they can be combined into ensembles. In the paper we combine specially modified Mamdani neuro-fuzzy systems into an AdaBoost ensemble.
Marcin Korytkowski, Leszek Rutkowski, Rafal Scherer   +2 more
openaire   +2 more sources