Name: RapidMiner Studio for Mac
Size: 175.3 MB
Developer: RapidMiner GmbH
Mac Platform: Intel
OS Version: OS X 10.8 or later
・Java 8 or later
・Online account to test the Professional edition
・Dual core 2 GHz processor
・4 GB RAM
・>1GB free disk space
Web Site: https://rapidminer.com/
Simplify the design of predictive analytics models and access numerous data loading, transformation, modeling and visualization methods, with the help of this powerful OS X app
RapidMiner Studio is a cross-platform application that aims to provide enterprises with an easy method of performing predictive analytics, with the help of an intuitive user interface.
Moreover, RapidMiner Studio does away with overly complex procedures and does not require any programming experience. Numerous data loading, modeling, transformation and visualization methods are provided, and you can work with extensive data sets.
Supports a wide variety of input data formats and offers an intuitive wizard mode
RapidMiner Studio can be very useful for business analysts, as it enables you to put the customer information you have already gathered to good use and make sure you do not lose your current clients.
To generate a prediction based on a set of user-provided variables, the necessary information first needs to be imported. The app supports a wide range of data formats, including Excel worksheets, XML documents, database tables and binary files.
To make this task easier, RapidMiner Studio offers an import wizard that guides you through the required steps.
Visualize data in multiple formats and generate graphical representations
Once the necessary data has been imported, you can take advantage of RapidMiner Studio’s numerous visualization modes, to learn information that may not have been evident at first glance.
The app can provide a summary of the source data and display charts that make it easier to compare certain parameters.
After analyzing the imported data, you can build a training model, by finding predictive relationships, and then apply it to your data set.
Create, apply and evaluate predictive models using your Mac
Then, to ensure the model accurately performs predictions, you can evaluate it with cross-validation,separating the source data into a certain number of parts, calculating performance for each of them, and then averaging the results from each test.
Overall, RapidMiner Studio is a powerful tool aimed at business analysts that can help you design predictive analytics models and put them to use within your company.
What’s new in RapidMiner Studio 7.4.0
February 14th, 2017
・Processes can now be executed in the background of Studio while you work on a different process in the user interface. This feature is only available for users with a Large license.
・New parallelized Loop operator.
・New parallelized Loop Values operator.
・New parallelized Loop Attributes operator.
・New parallelized Loop Files operator.
・Repository entries can now be sorted by date.
・Users with Large licenses can now grant additional permissions to unsigned extensions.
・Added a few new templates which can be used as a starting point when creating a new process.
・Improved performance of Polynominal Regression.
・Improved performance of Linear Regression.
・Improved error message in case a selected input attribute for an operator is of the wrong type.
・Improved operator progress for Generate Massive Data and several segmentation operators.
・Improved performance of LibSVM and Fast Large Margin when sparse input data is not in sparse data format.
・Small performance improvements for several operators that read parameters unnecessarily often.
・Performance improvement for operators that iterate over all attributes.
・Optimize by Generation (Evolutionary Aggregation) no longer shows unnecessary popup.
・Repository entry sorting by name now ignores capitalization.
・Users with Large licenses can now grant additional permissions to unsigned extensions via a new setting in the Start-up tab in the preferences.
・The Log table in the results panel now also uses the new UI look and feel.
・Fixed useless cipher error when starting Studio for the very first time.
・Fixed swapped title in models of Linear Discriminant Analysis and Quadratic Discriminant Analysis.
・Fixed side-effects of application of preprocessing models in other branches of the process.
・Fixed side-effects of Impute Missing Values in other branches of the process.
・Fixed wrong behavior when dismissing confirmation dialog asking for interruption of currently running process.
・Fixed Delete File not being able to handle relative paths.
・Meta data calculation of Generate Nominal Data can no longer cause freezing.
・Optimize by Generation (Evolutionary Aggregation) no longer does one iteration too much.
・Fixed Number of threads setting having no effect for Decision Tree and Random Forest if it was set to 1 and then increased again.
・Fixed rare error that could occur when displaying a grouped model in the results view.
・Added a temporary API for operators which should run in a parallelized fashion. Use the com.rapidminer.studio.concurrency.internal.ConcurrencyExecutionServiceProvider to access it.
・The existing Read SAS operator has been deprecated. There is a new SAS connector extension available on the Marketplace which provides an up-to-date replacement of the operator.
・Removed the compatibility level 7.1.1 of the operators Normalize, Replace Missing Values, Replace Infinite Values, Add Noise. These operators will no longer affect other branches of the progress even for processes created with compatibility level 7.1.0 or below.