Add to ORKGIn tbis paper, we propose two new nCllro-fIlZ7.} ' schemes, one for classification and one for clustering problems. The dassifLcatioll sclLeme is based all Simpson's Fuzzy Min Max method, <l.lld relaxes some a!iSlIffiptions he makes. This enables our scheme to handle mutually non exclusive classes. The neum-fuzzy clustering scheme is a ffililtircsolution algoritllm that is modeled after the mechanics or human pattern recognition. We also present data from an exhaustive comparison of these techniques with neural, statistical, machine learning and other traditional approaches to pattern recognition applications. The data ~ets lIscd for compariSOIl ~ incllIde tho~e from VCl's machine learning ccpo~itory. We lind tlLat OliC pr...
This paper presents a new neuro-fuzzy classifier, inspired by the Simpson's (1992, 1993) min-max mod...
In this work, we examine three softcomputing methodologies, i.e. rule based fuzzy classification sys...
One of the standard approaches for data analysis in unsupervised machine learning techniques is clus...
In this paper, we propose two new neuro--fuzzy schemes, one for classification and one for clusterin...
Neural networks and fuzzy techniques are among the most promising approaches to pattern recognition....
In our study, we proposed a novel Neuro-fuzzy classification technique for data mining. The inputs t...
AbstractIn our study, we proposed a novel Neuro-fuzzy classification technique for data mining. The ...
New approaches like neural networks and fuzzy sets have been used more and more in pattern recogniti...
Abstract:-In the paper we present a new class of neuro-fuzzy systems for pattern classification. The...
Over the last few decades, pattern classification has become one of the most important fields of art...
In this thesis we studied two of the most promising neural network classifiers called as fuzzy min-m...
Clustering and pattern recognition have been used for various purposes since times immemorial. Howev...
Clustering and pattern recognition have been used for various purposes since times immemorial. Howev...
Over the last few decades, pattern classification has become one of the most important fields of art...
At present, pattern classification is one of the most important aspects of establishing machine inte...
This paper presents a new neuro-fuzzy classifier, inspired by the Simpson's (1992, 1993) min-max mod...
In this work, we examine three softcomputing methodologies, i.e. rule based fuzzy classification sys...
One of the standard approaches for data analysis in unsupervised machine learning techniques is clus...
In this paper, we propose two new neuro--fuzzy schemes, one for classification and one for clusterin...
Neural networks and fuzzy techniques are among the most promising approaches to pattern recognition....
In our study, we proposed a novel Neuro-fuzzy classification technique for data mining. The inputs t...
AbstractIn our study, we proposed a novel Neuro-fuzzy classification technique for data mining. The ...
New approaches like neural networks and fuzzy sets have been used more and more in pattern recogniti...
Abstract:-In the paper we present a new class of neuro-fuzzy systems for pattern classification. The...
Over the last few decades, pattern classification has become one of the most important fields of art...
In this thesis we studied two of the most promising neural network classifiers called as fuzzy min-m...
Clustering and pattern recognition have been used for various purposes since times immemorial. Howev...
Clustering and pattern recognition have been used for various purposes since times immemorial. Howev...
Over the last few decades, pattern classification has become one of the most important fields of art...
At present, pattern classification is one of the most important aspects of establishing machine inte...
This paper presents a new neuro-fuzzy classifier, inspired by the Simpson's (1992, 1993) min-max mod...
In this work, we examine three softcomputing methodologies, i.e. rule based fuzzy classification sys...
One of the standard approaches for data analysis in unsupervised machine learning techniques is clus...