RapidMiner (formerly YALE) is a flexible Java environment for knowledge discovery in databases, machine learning, and data mining. Many nestable learning and preprocessing operators (including Weka) are provided. It features an XML-based graphical user interface, a plugin mechanism, and high-dimensional plotting, and provides an easy-to-use extension mechanism that makes it possible to integrate new operators and adapt the system to your personal requirements. A command line version is also included.
|Tags||education Information Management Scientific/Engineering Artificial Intelligence Adaptive Technologies Office/Business Database|
|Operating Systems||OS Independent Windows Unix|
Release Notes: The latest version of the Weka machine learning library was added, together with some other small additions and extensions. Several minor bugs were also fixed.
Release Notes: This release provides 13 new operators, more than 10 bugfixes, and a lot of exciting new features like the new operator “Script” allowing for arbitrary Groovy scripts, improvements for the join and the aggregation operators, faster name-based access of attributes, and several usability enhancements.
Release Notes: This release provides 35 new operators, more than 30 bugfixes, and many new features. New Preprocessing Options: removal of duplicates, nominal value splits, data set union and superset, and others. New Learning Schemes: linear and quadratic discriminant analysis, fast large margin, and others. New Process Possibilities: FileIterator, MacroConstruction, SetData, ExceptionHandling, and others. Improvements include better handling of time zones, helper operators for attribute renaming, and others.
Release Notes: This release focuses on the most requested data analysis, ETL, and BI requirements. It provides more than 50 new operators and a lot of new features including upgraded data pivotings, new aggregation functions, and date and time handling. The usage of function-based attribute construction was simplified, and optimized wizards or new visualizations, including zooming and panning, were added. More powerful processes are now possible due to enhanced macros and the new result storage mechanism. This release also provides fixes for more than 30 bugs.
Release Notes: This is a minor bugfix and feature release. In particular, two errors that caused problems in the new parameter optimization wizard for string and integer parameters were fixed. New features include a new 64-bit version for Windows x64 systems, multiple groupings for aggregations, better support for date and time columns, the grouping and ungrouping of models, and an improved attribute subset preprocessing. Additionally, the runtime of several analysis schemes was drastically reduced, in some cases up to a factor of 13.