Sign in to see all reviews and comparisons. It's Free!
By clicking Sign In with Social Media, you agree to let PAT RESEARCH store, use and/or disclose your Social Media profile and email address in accordance with the PAT RESEARCH Privacy Policy and agree to the Terms of Use.
ROSETTA is a toolkit for analyzing tabular data within the framework of rough set theory.
Category
Data Mining Software Free
Features
•Toolkit for analyzing tabular data within the framework of rough set theory •Intended as a general-purpose tool for discernibility-based modeling •Import/export – partial integration with DBMSs via ODBC •Completion of decision tables with missing values
License
Open Source
Price
Free
Pricing
Subscription
Free Trial
Available
Users Size
Small (<50 employees), Medium (50 to 1000 Enterprise (>1001 employees)
•Toolkit for analyzing tabular data within the framework of rough set theory •Intended as a general-purpose tool for discernibility-based modeling •Import/export – partial integration with DBMSs via ODBC
What are the benefits?
• Import/export • Preprocessing • Computation • Post processing • Validation and analysis
PAT Rating™
Editor Rating
Aggregated User Rating
Rate Here
Ease of use
7.6
7.0
Features & Functionality
7.6
8.5
Advanced Features
7.6
7.8
Integration
7.6
7.6
Performance
7.6
8.3
Customer Support
7.6
8.0
Implementation
8.2
Renew & Recommend
8.1
Bottom Line
ROSETTA is designed to support the overall data mining and knowledge discovery process: From initial browsing and preprocessing of the data, via computation of minimal attribute sets and generation of if-then rules or descriptive patterns, to validation and analysis of the induced rules or patterns.
7.6
Editor Rating
8.0
Aggregated User Rating
3 ratings
You have rated this
ROSETTA is a toolkit for analyzing tabular data within the framework of rough set theory. It is designed for supporting the overall data mining and knowledge discovery process: From initial browsing and preprocessing of the data, via computation of minimal attribute sets and generation of if-then rules or descriptive patterns, to validation and analysis of the induced rules or patterns.
This toolkit is not specifically towards any particular application domain, it is intended as a general-purpose tool for discernibility-based modeling. Highly intuitive GUI environment is offered and in this environment data-navigational abilities are emphasized. The main orientation of GUI is representing all manipulable objects as individual GUI items, each with their own set of context-sensitive menus.
Rosetta toolkit has several features such as: import/export – partial integration with DBMSs via ODBC, exporting of rules, reducts, tables, graphs and other objects to various formats, including XML, C++ and Prolog; preprocessing – completion of decision tables with missing values, discretization of numerical attributes; computation – support for both unsupervised and supervised learning, support for user-defined notions of discernibility, efficient computation of exact or approximate reducts, for various types of discernibility.
Generation of if-then rules or descriptive patterns via reducts, execution of script files, support for cross-validation; postprocessing – advanced filtering of sets of reducts and rules; validation and analysis – application of synthesized rules to unseen examples, generation of confusion matrices.
ROC curves and calibration curves, evaluation of individual rules according to advanced measures of quality; miscellaneous – clustering via tolerance relations, computation of partitions and variable precision rough set approximations, support for random sampling of observations.
Rosetta is mainly to be used as a general-purpose tool for specifically discernibility-based modelling.
Company size
Medium (50 to 1000)
User Role
End User
User Industry
Education
Rating
Ease of use8.3
Rosett provides very nice and intuitive GUI interface which emphasizes data-navigational abilities. The GUI is very object-oriented. This just means that all the objects are shown as individual GUI items and each one of them has a set of context-sensitive menus. It also has a computational kernel that can found as a command-line program.
Features & Functionality8.5
Advanced Features7.8
Integration7.6
Performance8.3
Training 8.1
Customer Support8
Implementation8.2
Renew & Recommend8.1
ADDITIONAL INFORMATION Rosetta works within the framework of rough set theory, as a toolkit for analyzing tabular data. It’s mainly designed for supporting the entire data mining and knowledge discovery process.
Discernibility-based modelling.
Rosetta is mainly to be used as a general-purpose tool for specifically discernibility-based modelling.
Medium (50 to 1000)
End User
Education
Rosett provides very nice and intuitive GUI interface which emphasizes data-navigational abilities. The GUI is very object-oriented. This just means that all the objects are shown as individual GUI items and each one of them has a set of context-sensitive menus. It also has a computational kernel that can found as a command-line program.
ADDITIONAL INFORMATION
Rosetta works within the framework of rough set theory, as a toolkit for analyzing tabular data. It’s mainly designed for supporting the entire data mining and knowledge discovery process.