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Pattern Recognition with Fuzzy Objective Function Algorithms
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Citations
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Self-organizing neural network as a fuzzy classifier
Sushmita Mitra,Sankar K. Pal +1 more
TL;DR: ASelf-organizing artificial neural network, based on Kohonen's model of self-organization, which is capable of handling fuzzy input and of providing fuzzy classification and the effectiveness of this algorithm is demonstrated on the speech recognition problem for various network array sizes, training sets and gain factors.
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Gene Expression Profile Classification: A Review
TL;DR: This review attempted to present a unified approach that considers both class-prediction and class-discovery, and discussed important issues such as preprocessing of gene expression data, curse of dimensionality, feature extraction/selection, and measuring or estimating classifier performance.
Journal ArticleDOI
A Neuro–Fuzzy Inference System for sEMG-Based Identification of Hand Motion Commands
Mahdi Khezri,Mehran Jahed +1 more
TL;DR: A multistep-based sEMG pattern-recognition system where, in each step, a stronger more capable relevant technique with a noticeable improved performance is employed is employed.
Journal ArticleDOI
Survey of State-of-the-Art Mixed Data Clustering Algorithms
Amir Ahmad,Shehroz S. Khan +1 more
TL;DR: A taxonomy for the study of mixed data clustering algorithms by identifying five major research themes is presented in this article. But it is difficult to directly apply mathematical operations, such as summation or averaging, to the feature values of these datasets.
Journal ArticleDOI
Collaborative clustering with the use of Fuzzy C-Means and its quantification
Witold Pedrycz,Partab Rai +1 more
TL;DR: This study develops a comprehensive optimization scheme and discusses its two-phase character in which the communication phase of the granular findings intertwines with the local optimization being realized at the level of the individual site and exploits the evidence collected from other sites.
References
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Journal ArticleDOI
Nearest neighbor pattern classification
Thomas M. Cover,Peter E. Hart +1 more
TL;DR: The nearest neighbor decision rule assigns to an unclassified sample point the classification of the nearest of a set of previously classified points, so it may be said that half the classification information in an infinite sample set is contained in the nearest neighbor.
Book
Introduction to Statistical Pattern Recognition
TL;DR: This completely revised second edition presents an introduction to statistical pattern recognition, which is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field.
A fuzzy relative of the isodata process and its use in detecting compact well-separated clusters
TL;DR: In this paper, two fuzzy versions of the k-means optimal, least squared error partitioning problem are formulated for finite subsets X of a general inner product space, and the extremizing solutions are shown to be fixed points of a certain operator T on the class of fuzzy, k-partitions of X, and simple iteration of T provides an algorithm which has the descent property relative to the LSE criterion function.