Clustering of Time Series Subsequences is Meaningless
... series, or a single time series, from which individual time series are extracted with a sliding window. Given the recent explosion of interest in streaming data and online algorithms, the latter case has received much attention. In this work we make a surprising claim. Clustering of streaming time s ...
... series, or a single time series, from which individual time series are extracted with a sliding window. Given the recent explosion of interest in streaming data and online algorithms, the latter case has received much attention. In this work we make a surprising claim. Clustering of streaming time s ...
Survey on Outlier Detection in Data Mining
... clusters are then determined and considered as outlier clusters and after that the rest of outliers (if any) are then detected based on calculating the absolute distances between the medoid of the current cluster and each one of the points in the same cluster [13]. Ms. S. D. Pachgade and Ms. S. S. D ...
... clusters are then determined and considered as outlier clusters and after that the rest of outliers (if any) are then detected based on calculating the absolute distances between the medoid of the current cluster and each one of the points in the same cluster [13]. Ms. S. D. Pachgade and Ms. S. S. D ...
Clustering Marketing Datasets with Data Mining Techniques
... the same dataset external representation format. So, it can easily be downloaded from Internet, used without data format problems and, if required, changed using the same programming language (Romero et al., 2007). Weka (Witten & Frank, 2005) is open source software which contains a collection of ma ...
... the same dataset external representation format. So, it can easily be downloaded from Internet, used without data format problems and, if required, changed using the same programming language (Romero et al., 2007). Weka (Witten & Frank, 2005) is open source software which contains a collection of ma ...
Open Access
... The telecom industry is a highly competitive market, with frequent innovations required to sustain the business. The current business situation indicates a mismatch between user expectations and tariff plans available in the market. Furthermore, most service providers suffer from a high churn rate. ...
... The telecom industry is a highly competitive market, with frequent innovations required to sustain the business. The current business situation indicates a mismatch between user expectations and tariff plans available in the market. Furthermore, most service providers suffer from a high churn rate. ...
Pattern Recognition Techniques in Microarray Data Analysis
... Hierarchical Clustering: There are various hierarchical clustering algorithms that can be applied to microarray data analysis. These include single-linkage clustering, complete-linkage clustering, averagelinkage clustering, weighted pair-group averaging, and within pair-group averaging [17,20-22]. T ...
... Hierarchical Clustering: There are various hierarchical clustering algorithms that can be applied to microarray data analysis. These include single-linkage clustering, complete-linkage clustering, averagelinkage clustering, weighted pair-group averaging, and within pair-group averaging [17,20-22]. T ...
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.