Open AccessBook
Pattern Recognition with Fuzzy Objective Function Algorithms
Reads0
Chats0
TLDR
Books, as a source that may involve the facts, opinion, literature, religion, and many others are the great friends to join with, becomes what you need to get.Abstract:
New updated! The latest book from a very famous author finally comes out. Book of pattern recognition with fuzzy objective function algorithms, as an amazing reference becomes what you need to get. What's for is this book? Are you still thinking for what the book is? Well, this is what you probably will get. You should have made proper choices for your better life. Book, as a source that may involve the facts, opinion, literature, religion, and many others are the great friends to join with.read more
Citations
More filters
Journal ArticleDOI
An entropy criterion for assessing the number of clusters in a mixture model
Gilles Celeux,Gilda Soromenho +1 more
TL;DR: In this article, an entropy criterion is proposed to estimate the number of clusters arising from a mixture model, which is derived from a relation linking the likelihood and the classification likelihood of a mixture.
Journal ArticleDOI
Review: A review of novelty detection
TL;DR: This review aims to provide an updated and structured investigation of novelty detection research papers that have appeared in the machine learning literature during the last decade.
Journal ArticleDOI
The role of fuzzy logic in the management of uncertainty in expert systems
TL;DR: F fuzzy logic is suggested, which is the logic underlying approximate or, equivalently, fuzzy reasoning, which leads to various basic syllogisms which may be used as rules of combination of evidence in expert systems.
Journal ArticleDOI
DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction
Nikola Kasabov,Qun Song +1 more
TL;DR: It is demonstrated that DENFIS can effectively learn complex temporal sequences in an adaptive way and outperform some well-known, existing models.
Journal ArticleDOI
Time-series clustering - A decade review
TL;DR: This review will expose four main components of time-series clustering and is aimed to represent an updated investigation on the trend of improvements in efficiency, quality and complexity of clustering time- series approaches during the last decade and enlighten new paths for future works.
References
More filters
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.