Viscovery SOMine is available for Windows 10 and Windows 11. The Viscovery One(2)One Engine is also available on Linux (Ubuntu 22.04).

Starting with version 8.0, Viscovery Software is only available as 64-bit versions.

Yes, you can download the free module Visual Explorer of Viscovery SOMine here.

For technical support, send an email to support@viscovery.net.

Viscovery is only available as a download package.

The manuals are available in English and Japanese languages, as is Viscovery software.

There are 2 to 3 patch releases per year that mostly include bug fixes. One minor feature release is planned every year. Major feature releases are planned every 2 years.

The most popular site is probably the UCI KDD Archive from University of California with the UCI Machine Learning Repository cited therein.

Many other sites also offer a variety of data sets. Here are a few to get you started:

• StatLib---Datasets Archive from Carnegie Mellon University
• Datasets for Data Mining, Analytics and Knowledge Discovery at KDnuggets
• Datasets for Data Mining from University of Edinburgh

View the application demos and the software demo of Viscovery SOMine on the Viscovery website. Further examples with tips and tricks are part of our training courses.

First, familiarize yourself with self-organizing maps (SOMs) and how to read and interpret them.

To try out Viscovery SOMine, download the free module Visual Explorer of Viscovery SOMine.

Watch the software demo of Viscovery SOMine, which shows all steps in the process of map creation.

Using a simple and small data set that you are familiar with, repeat the workflows step by step with your data.

Contact support@viscovery.net for open questions.

For more involved applications, Viscovery also offers consulting support and training courses.

Yes, you can. All you need to know is how to read a SOM.

In Viscovery, users are shielded from the technology, as they are guided by an easy-to-use workflow-oriented interface. Proven default settings have been established so that novice users can get useful results. Of course, the more the user understands the process and the technology, the more he or she can control the process.

Even though you do not have to be a SOM expert, a basic knowledge of data mining is necessary to be able to work with SOMs in a useful manner. In particular, “garbage in – garbage out”, the first paradigm, is as true for data mining with SOMs as it is for other data mining methods. Equally important, “know your data”, the second paradigm, holds true for SOMs as well as for any other data mining methods.

You can use Viscovery even if you do not understand much about statistics. The unique visualization of the resulting maps can easily be understood by non-statisticians. For statistically skilled users, Viscovery provides a variety of statistical tools to evaluate data in addition to the SOM.

Keep in mind that even though you do not know much about statistics, you do have to know a lot about your data before you can produce meaningful results with SOMs.

Viscovery provides numerous preprocessing functions, including the following:

• Transformations of variables
• Replacements of values
• Treatment of (multi-valued) nominal attributes
• Definition of new attributes depending on existing ones using built-in formulas and R scripts
• Handling of missing values
• Outlier treatment
• Removal of data records
• Sampling of data

The statistical analysis functions provided by Viscovery include the following:

• Descriptive statistics
• Correlation analysis
• Histograms
• Frequency tables
• Box plots
• Scatter plots
• Principal components analysis
• Regression analyses