RapidMiner is a data science software platform developed by the company of the same name that provides an integrated environment for automatic learning, deep learning, text mining and predictive analytics. It is used for business and commercial applications, as well as for research, education, training, rapid prototyping and application development and supports all the steps of the machine learning process, including data preparation, visualization of results, Validation and optimization. RapidMiner is developed on an open-core model. The basic edition of RapidMiner (free), which is limited to 1 logical processor and 10,000 rows of data, is available under the AGPL license. Commercial prices start at $ 2,500 and are available from the developer.
History
RapidMiner, formerly known as YALE (Other Learning Environment), was developed from 2001 by Ralf Klinkenberg, Ingo Mierswa and Simon Fischer in the Artificial Intelligence Unit of the Technical University of Dortmund. As of 2006, its development was driven by Rapid-I, a company founded by Ingo Mierswa and Ralf Klinkenberg in the same year. In 2007, the name of the software was changed from YALE to RapidMiner. In 2013, the company changed its name from Rapid-I to RapidMiner.
Description
RapidMiner uses a client / server model with the server offered as a premise in public or private cloud infrastructure. According to Bloor Research, RapidMiner provides 99% of an advanced analytics solution through template-based frameworks that accelerate delivery and reduce errors by eliminating almost the need to write code. RapidMiner provides data extraction and machine learning procedures, including: data loading and transformation (extraction, transformation, load (ETL)), preprocessing and visualization of data, predictive analysis and statistical modeling, evaluation and implementation. RapidMiner is written in the Java programming language. RapidMiner provides a GUI for designing and executing analytical workflows. These workflows are called "Processes" in RapidMiner and consist of multiple "Operators". Each operator performs a single task within the process, and the output of each operator forms the input of the next. Alternatively, the engine can be called from other programs or used as an API. Individual functions can be called from the command line. RapidMiner provides learning schemes, models and algorithms and can be extended using R and Python scripts.
The functionality of RapidMiner can be extended with additional add-ons that are available through RapidMiner Marketplace. The RapidMiner Marketplace provides a platform for developers to create data analysis algorithms and publish them in the community. With version 7.0, RapidMiner included updates of its introduction materials, an updated user interface and improvements in its data preparation capabilities.