Journal ArticleDOI
Validity index for crisp and fuzzy clusters
TLDR
A cluster validity index and its fuzzification is described, which can provide a measure of goodness of clustering on different partitions of a data set, and results demonstrating the superiority of the PBM-index in appropriately determining the number of clusters are provided.About:
This article is published in Pattern Recognition.The article was published on 2004-03-01. It has received 710 citations till now. The article focuses on the topics: Fuzzy clustering & Correlation clustering.read more
Citations
More filters
Journal ArticleDOI
Long-Term Activity Recognition from Wristwatch Accelerometer Data
TL;DR: This work used acceleration data from a wristwatch in order to identify long-term activities, and compares the use of Hidden Markov Models and Conditional Random Fields for the segmentation task.
Journal ArticleDOI
Topology-Based Hierarchical Clustering of Self-Organizing Maps
TL;DR: This paper proposes an automated clustering method for SOMs, which is a hierarchical agglomerative clustering of CONN, and shows that, for the datasets used in this paper, data-topology-based hierarchical clustering can produce better partitioning than hierarchical clusters based solely on distance information.
Journal ArticleDOI
Segmentation performance evaluation for object-based remotely sensed image analysis
TL;DR: A novel metric, known as the spatial unsupervised (SU) metric, which meets both the requirements and the importance of these is illustrated by the poor performance of a metric which fails to meet them both.
Journal ArticleDOI
A Cluster-Validity Index Combining an Overlap Measure and a Separation Measure Based on Fuzzy-Aggregation Operators
H. Le Capitaine,Carl Frélicot +1 more
TL;DR: A CV index is presented that helps to find the optimal number of clusters of data from partitions generated by a fuzzy-clustering algorithm, such as the fuzzy c-means (FCM) or its derivatives.
Journal ArticleDOI
Evolution-Based Tabu Search Approach to Automatic Clustering
Shih-Ming Pan,Kuo-Sheng Cheng +1 more
TL;DR: This work proposes a framework of automatic clustering algorithms (called ETSAs) that do not require users to give each possible value of required parameters (including the number of clusters) and demonstrates the superiority of the ETSA in finding the correct number of cluster while constructing clusters with good validity.
References
More filters
Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Genetic algorithms in search, optimization and machine learning
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Book
Applied Multivariate Statistical Analysis
R. A. Johnson,Dean W. Wichern +1 more
TL;DR: In this article, the authors present an overview of the basic concepts of multivariate analysis, including matrix algebra and random vectors, as well as a strategy for analyzing multivariate models.
Journal ArticleDOI
Applied Multivariate Statistical Analysis.
TL;DR: In this article, the authors present an overview of the basic concepts of multivariate analysis, including matrix algebra and random vectors, as well as a strategy for analyzing multivariate models.