Today, the free open-source Data Mining software is one of the world-wide most widely used Data Mining solutions. Among the large amount of users, many of them already (or will) use RapidMiner every day and are able to master the basic operations and Data Mining processes. On the other hand, RapidMiner is also the Data Mining application with the largest functionality and probably also with the highest degree of complexity. The reasons for the latter is the large amount of combinations and possibilities for the analyst. This course helps intermediate learners to understand and to deploy complex Data Mining processes.

This seminar covers the automatic optimization of parameters, the optimization of the process structure itself, extended possibilities for guided feature selection and feature construction, the collection of process statistics, extended control of inputs and outputs, the definition and usage of macros, cost-sensitive learning and other meta learning schemes, changes for the prediction thresholds of classification models, loops in processes and other meta operations, complex filter operations, as well as support for data related tasks like directly working on databases together with the identification of appropriate operators for this. A high level of lively discussions and exchanges between the participants is encouraged. Goal of this seminar is that all participants will be enabled to transfer the gained knowledge to own data mining problems and solve them quickly and easily. This should be also achieved by a high number of practical exercises.

Details

• Course ID: 1301
• Number of days: 2 days
• Location: Dortmund, Germany
• Target audience: users, analysts, developers, administrators
• Previous knowledge: basic knowledge of Data Mining with RapidMiner (otherwise we recommend the visit of one of our introduction courses)
• Methods: lectures, discussions, individual and group work, exercises on realistic data. 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 is a compact introduction into the foundations of data mining and into the software RapidMiner. It addresses intermediate learners and professionals. Topics of this course are
  • Automatic optimization of parameters
  • Automatic optimization of the process structure
  • Extended possibilities for guided feature selection
  • Feature Construction
  • Process logging
  • Extended control of inputs and outputs
  • The definition and usage of macros
  • Loops and other meta operations
  • Changing the prediction threshold for binary classification problems
  • Cost-sensitive learning and other meta learning schemes
  • Complex filter operations
  • Support for directly working on databases and identification of appropriate operators
  Extensive exercises on different data sets will be performed for all topics.

Prices

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