Results 221 to 230 of about 21,297 (247)

Applications of Deep Rule-Based Classifiers

2018
In this chapter, the algorithm summary of the main procedure of the deep rule-based (DRB) classifier described in Chap. 9 is provided. Numerical examples based on popular benchmark image sets including, handwritten digits recognition, remote sensing scene classification, face recognition and object recognition, etc., are presented for evaluating the ...
Angelov, P.P., Gu, X.
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Classification Confidence Of Fuzzy Rule-Based Classifiers

ECMS 2011 Proceedings edited by: T. Burczynski, J. Kolodziej, A. Byrski, M. Carvalho, 2011
In this paper we first introduce the concept of classification confidence in fuzzy rule-based classification. Classification confidence shows the strength of classification for an unseen pattern. Low classification confidence for an unseen pattern means that the classification of that pattern is not very clear compared to that with high classification ...
Tomoharu Nakashima, Ashish Ghosh
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Providing PRTools with fuzzy rule-based classifiers

International Conference on Fuzzy Systems, 2010
This paper first reviews the state-of-the-art of fuzzy rule-based classifiers (FRBCs), then it discusses how to implement an FRBC under the Pattern Recognition Toolbox (PRTools), the de-facto standard toolbox for classification in Matlab. Such an implementation, called frbc, allows for a straightforward comparison of frbc with other classifiers already
COCOCCIONI, MARCO, D'ANDREA, ELEONORA, LAZZERINI, BEATRICE   +2 more
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GPGPU Implementation of Fuzzy Rule-Based Classifiers

2012
This paper presents a parallel implementation of fuzzy-rule-based classifiers using a GPGPU (General Purpose Graphics Processing Unit). There are two steps in the process of fuzzy rule-based classification: Fuzzy-rule generation from training data and classification of an unseen input pattern.
Tomoharu Nakashima, Keigo Tanaka, Noriyuki Fujimoto, Ryosuke Saga   +3 more
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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
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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.
MENCAR, CORRADO, CASTIELLO, CIRO, FANELLI, Anna Maria   +2 more
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Visualization of Rules in Rule-Based Classifiers

2012
Interpretation and visualization of the classification models are important parts of machine learning. Rule-based classifiers often contain too many rules to be easily interpreted by humans, and methods for post-classification analysis of the rules are needed. Here we present a strategy for circular visualization of sets of classification rules.
Susanne Bornelöv, Stefan Enroth, Jan Komorowski   +2 more
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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
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Ensembling Rule Based Classifiers for Detecting Network Intrusions

2009 International Conference on Advances in Recent Technologies in Communication and Computing, 2009
An intrusion is defined as a violation of the security policy of the system, and hence, intrusion detection mainly refers to the mechanisms that are developed to detect violations of system security policy. Recently, data mining techniques have gained importance in providing the valuable information which in turn can help to enhance the decision on ...
Mrutyunjaya Panda, Manas Ranjan Patra
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Clustering Based on Fuzzy Rule-Based Classifier

2014
Clustering is the unsupervised classification of patterns which has been addressed in many contexts and by researchers in many disciplines. Fuzzy clustering is recommended than crisp clustering when the boundaries among the clusters are vague and uncertain. Popular clustering algorithms are K-means, K-medoids, Hierarchical Clustering, fuzzy-c-means and
D. K. Behera, P. K. Patra
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