- UUM Electronic Theses and Dissertation
... Advances in digital technology and the World Wide Web has led to the increase of digital documents that are used for various purposes such as publishing and digital library.This phenomenon raises awareness for the requirement of effective techniques that can help during the search and retrieval of t ...
... Advances in digital technology and the World Wide Web has led to the increase of digital documents that are used for various purposes such as publishing and digital library.This phenomenon raises awareness for the requirement of effective techniques that can help during the search and retrieval of t ...
Pattern Recognition and Classification for Multivariate - DAI
... Our main interest is the recognition of patterns, or rather situations, in sensor data recorded during a car drive. To identify recurring situations we need to group the identified segments according their similarity. For the grouping of time series segments we propose agglomerative hierarchical clu ...
... Our main interest is the recognition of patterns, or rather situations, in sensor data recorded during a car drive. To identify recurring situations we need to group the identified segments according their similarity. For the grouping of time series segments we propose agglomerative hierarchical clu ...
paper
... this area [55, 62, 54, 33]. Recent work includes [7, 58, 1, 2, 4]. Though there are approaches to evaluate several or all levels of the hierarchy [23], there has never been a systematic, numerical methodology of evaluating such hierarchical clusterings as hierarchies. The cluster hierarchy can be us ...
... this area [55, 62, 54, 33]. Recent work includes [7, 58, 1, 2, 4]. Though there are approaches to evaluate several or all levels of the hierarchy [23], there has never been a systematic, numerical methodology of evaluating such hierarchical clusterings as hierarchies. The cluster hierarchy can be us ...
A Survey: Outlier Detection in Streaming Data Using
... minera method. This is a clustering based approach for the outlier detection which is based on the k-mean. This method divides data stream in the chunks for the further processing. Yogita has proposed a framework for outlier detection in evolving data streams by weighting attributes in clustering. T ...
... minera method. This is a clustering based approach for the outlier detection which is based on the k-mean. This method divides data stream in the chunks for the further processing. Yogita has proposed a framework for outlier detection in evolving data streams by weighting attributes in clustering. T ...
Classification and Clustering - Connected Health Summer School
... – This is not easy to stipulate and often not appropriate for a business application. – We can try an initial value of k and inspect the clusters that are obtained • then repeat, if necessary, with a different value of k. ...
... – This is not easy to stipulate and often not appropriate for a business application. – We can try an initial value of k and inspect the clusters that are obtained • then repeat, if necessary, with a different value of k. ...
Nearest-neighbor chain algorithm
In the theory of cluster analysis, the nearest-neighbor chain algorithm is a method that can be used to perform several types of agglomerative hierarchical clustering, using an amount of memory that is linear in the number of points to be clustered and an amount of time linear in the number of distinct distances between pairs of points. The main idea of the algorithm is to find pairs of clusters to merge by following paths in the nearest neighbor graph of the clusters until the paths terminate in pairs of mutual nearest neighbors. The algorithm was developed and implemented in 1982 by J. P. Benzécri and J. Juan, based on earlier methods that constructed hierarchical clusterings using mutual nearest neighbor pairs without taking advantage of nearest neighbor chains.