The course "Data Mining for Developers: Extending RapidMiner and Integration as a Data Mining Engine" aims at software developers and analysts with background knowledge in development. Compared with proprietary solutions, using an open-source software like RapidMiner has the big advantage that missing functions can easily be added. Therefore, the course gives a step-by-step introduction showing how new methods and operators can be integrated into the software. Starting with basic instructions for the setup of the development environment (IDE), the complete development and integration of an operator is performed. This enables you to develop specialized solutions for your data and use them directly in RapidMiner. In particular, all participants will also learn how the data can be effectively managed and transformed.

However, RapidMiner is not only a data mining application but also a complete data mining library which can be integrated into your own software. The second part of this course hence deals with the integration of RapidMiner into other software products. This allows, for example, the application of learned models with one simple click for non-analysts or the addition of adaptive behavior to your products. All necessary steps will be discussed at hand of a simple but complete integration example.

Details

• Course ID: 1303
• Number of days: 2 days
• Location: Dortmund, Germany
• Target audience: developers, analysts with background in development, administrators
• Previous knowledge: knowledge of programming in Java, basic knowledge of data mining, knowledge of RapidMiner
• Methods: lectures, discussions, individual and group work, implementation of practical exercises. Participants may introduce own work and project specific questions in order to find particular solutions together with the trainer and other participants.
• Content: this course provides a compact introduction into the foundations of the programming of new data mining methods and their integration into RapidMiner as well as the integration of RapidMiner as a Java data mining library. Topics of this course are
  • Setting up an IDE for the programming for RapidMiner
  • Structure of RapidMiner
  • Basics of operator programming
  • Definition of parameter types
  • Definition of in- and output conditions
  • Basics of programming operator chains
  • Definition of conditions for inner operators
  • Logging
  • Value Logging
  • Data management in and with RapidMiner
  • Iterations over data sets
  • Data set transformations
  • Integrating new operators
  • Programming and creating plugins
  • Legal questions and license conditions
  • RapidMiner as a free Java Data Mining Library
  • Conditions for the integration of RapidMiner
  • Initializing the library
  • Using predefined processes
  • Using single operators
  • Managements of the data flow and of in- and outputs
  • In- and output of results
  • External logging
  • Memory efficient optimization of the library
  Extensive exercises will be performed.

Prices

Value added tax (VAT) may have to be added to these prices.