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CLUTO is a software package for clustering low- and high-dimensional datasets and for analyzing the characteristics of the various clusters.
Category
Data Mining Software Free
Features
•Intended for clustering low- and high-dimensional datasets and for analyzing the characteristics of the various clusters •Multiple classes of clustering algorithms •Multiple methods for effectively summarizing the clusters •Can scale to very large datasets
License
Open Source
Price
Free
Pricing
Subscription
Free Trial
Available
Users Size
Small (<50 employees), Medium (50 to 1000 Enterprise (>1001 employees)
•Intended for clustering low- and high-dimensional datasets and for analyzing the characteristics of the various clusters •Multiple classes of clustering algorithms •Multiple methods for effectively summarizing the clusters •Can scale to very large datasets
What are the benefits?
• Can scale to very large datasets containing hundreds of thousands of objects and tens of thousands of dimensions. • Multiple methods for effectively summarizing the clusters. • Extensive cluster visualization capabilities and output options. • Numerous novel clustering criterion functions and agglomerative merging schemes. • Multiple similarity/distance functions. • Multiple classes of clustering algorithms.
PAT Rating™
Editor Rating
Aggregated User Rating
Rate Here
Ease of use
7.6
9.0
Features & Functionality
7.6
9.0
Advanced Features
7.6
9.2
Integration
7.6
9.4
Performance
7.6
9.3
Customer Support
7.6
9.2
Implementation
8.5
Renew & Recommend
9.2
Bottom Line
CLUTO is well-suited for clustering data sets arising in many diverse application areas including information retrieval, customer purchasing transactions, web, GIS, science, and biology.CLUTO's distribution consists of both stand-alone programs and a library via which an application program can access directly the various clustering and analysis algorithms implemented in CLUTO.
7.6
Editor Rating
9.0
Aggregated User Rating
2 ratings
You have rated this
Cluto is software package intended for clustering low- and high-dimensional datasets and for analyzing the characteristics of the various clusters. It is well-suited for clustering data sets, arisen in many diverse application areas including information retrieval, customer purchasing transactions, web, GIS, science, and biology.
CLUTO's distribution consists of both stand-alone programs and a library via which an application program can access directly the various clustering and analysis algorithms implemented in CLUTO. This software has several features such as multiple classes of clustering algorithms – partitional, agglomerative, & graph-partitioning based; multiple similarity/distance functions – Euclidean distance, cosine, correlation coefficient, extended Jaccard, user-defined; numerous novel clustering criterion functions and agglomerative merging schemes;.
Traditional agglomerative merging schemes – single -link, complete-link, UPGMA; extensive cluster visualization capabilities and output options – postscript , SVG, gif, xfig, etc; multiple methods for effectively summarizing the clusters – most descriptive and discriminating dimensions, cliques, and frequent itemsets; can scale to very large datasets containing hundreds of thousands of objects and tens of thousands of dimensions.
This software has a cross-platform graphical application called gCLUTO, for clustering low- and high-dimensional datasets and for analyzing the characteristics of the various clusters. This app is build on-top of the CLUTO clustering library and it provides tools for visualizing the resulting clustering solutions using tree, matrix, and an OpenGL-based mountain visualization.
Cluto also has a web-enabled data clustering application, called wCLUTO, designed for the clustering and data-analysis requirements of gene-expression analysis and it is just like gCLUTO it is build on top of the CLUTO clustering library, so users can upload their datasets, select from a number of clustering methods, perform the analysis on the server, and visualize the final results.
For analyzing the characteristics of different clusters
What are the benefits?
The application areas include, retrieval of information, customer purchasing transactions, web, GIS, science, and biology.
Company size
Medium (50 to 1000)
User Role
Super User
User Industry
Energy
Rating
Ease of use7.9
CLUTO is an excellent data mining software package for analyzing the characteristics of different clusters, specifically for low and high dimensional datasets. In addition, it also analyzes characteristics of the different clusters. It does this very well. CLUTO works very well in terms of clustering data sets which arise in different application areas.
Features & Functionality8
Advanced Features8.4
Integration8.7
Performance8.5
Training 8.3
Customer Support8.3
Implementation8.5
Renew & Recommend8.3
ADDITIONAL INFORMATION CLUTO is able to scale to datasets that are very large. The software has gCLUTO which is a cross-platform graphical application. gCLUTO is used for clustering low and high-dimensional data sets. In addition to gCLUTO, CLUTO also has wCLUTO which is web-enabled data clustering app which is designed for data-analysis requirements.
For analyzing the characteristics of different clusters
The application areas include, retrieval of information, customer purchasing transactions, web, GIS, science, and biology.
Medium (50 to 1000)
Super User
Energy
CLUTO is an excellent data mining software package for analyzing the characteristics of different clusters, specifically for low and high dimensional datasets. In addition, it also analyzes characteristics of the different clusters. It does this very well. CLUTO works very well in terms of clustering data sets which arise in different application areas.
ADDITIONAL INFORMATION
CLUTO is able to scale to datasets that are very large. The software has gCLUTO which is a cross-platform graphical application. gCLUTO is used for clustering low and high-dimensional data sets. In addition to gCLUTO, CLUTO also has wCLUTO which is web-enabled data clustering app which is designed for data-analysis requirements.