RapidMiner Studio
RapidMiner Studio
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RapidMiner Studio free download for Mac

RapidMiner Studio

Version 9.10.1

Comprehensive data science platform with visual workflow design and full automation.

RapidMiner Studio overview

RapidMiner Studio is a comprehensive data science platform with visual workflow design and full automation


Visual Workflow Designer

Increase productivity across the entire data science team, from analysts to experts

Connect to Any Data Source

Work with all of your data, no matter where it lives

Automated In-Database Processing

Run data prep and ETL inside databases to keep your data optimized for advanced analytics

Data Visualization & Exploration

Evaluate data health, completeness, and quality

Data Prep & Blending

Eliminate the hassle of preparing data for predictive modeling

Visual & Automated Machine Learning

Quickly create impactful machine learning models without writing code

Model Validation

Understand the true performance of a model before deploying to production

Explainable Models Not Black Boxes

Create visual data science workflows that are easy to explain and easy to understand

Get More From R & Python Code

Scalable code deployment and collaboration between coders and non-coders

Flexible Scoring & Model Operations

Turn predictive insights into business impact

Automation & Process Control

Build sophisticated visual workflows and automate important tasks

Open & Extensible

Integrate with existing applications and code

What’s new in version 9.10.1

Updated on Oct 26 2021

Version 9.10.1:
  • Improved potential bias detection by producing less false positives
  • Added further explanations in the bias warning tooltip to help educate users better about why it occurred - and what can be done to mitigate the problem
  • Replaced DBSCAN operator by new version
  • Deprecated Expectation Maximization Clustering operator
  • Improved/minimized operator instantiation for documentation/search, leading to a reduced startup time
  • Fixed metadata of Apply Model in rare cases
  • Fixed wrong results after applying the Single Rule Induction model in case of a different ordering of the columns
  • Single Rule Induction model can now be stored in the repository
  • Fixed wrong results after applying the Subgroup Discovery model in case of a different ordering of the columns
  • Fixed table capability store/retrieve in signatures
  • Fixed wrong URL when opening the link in project connections when using AI Hub vault injections
  • Time Series: Fixed a bug in Process Windows which caused an Exception for input data which has long gaps and if the parameter "empty window handling" is set to skip
  • Time Series: Fixed a bug in Holt-Winters when the input data contains a section with 0 as values, or if every n.th value in 0 (with n being the period).
  • section with 0 as values will be ignored in the smoothing of the seasonal component in holt-Winters
  • every n.th value is 0 (with n being the period) will result in an UserError for the multiplicative seasonality model





303.7 MB



App requirements

  • Intel 64
  • OS X 10.8.0 or later
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