KohonenF08

Fortran KohonenF08 API Documentation

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Goals and Motivation

Self-Organizing Maps or Kohonen Maps are powerful computational tools to cluster multivariate data using a topology preservation approach, that is, the clustering obtained by using this methodology is designed to preserve neighboring relationships between samples (closer samples in the input space remain closer in the output space).

Two Level Self-Organizing Maps are important in many applied areas but currently there is not a proper implementation that suited my needs. So I decided to implement this clustering approach in Fortran using the features included in the new standard Fortran2008. This ensures computational efficiency and software extensibility, in addition to having to learn more about Fortran.

Scope

The goal of the KohonenF08 Library is to achieve the following general scope:

• Data transformation (normal and uniform standarization)
• Clustering using Self-Organizing Maps with one a several layers
• Clustering using VISOM

Code of Conduct

In the interest of fostering an open and welcoming environment, we as contributors and maintainers pledge to make participation in our project and our community a harassment-free experience for everyone, regardless of age, body size, disability, ethnicity, gender identity and expression, level of experience, nationality, personal appearance, race, religion, or sexual identity and orientation.

License

The KohonenF08 source code and related files and documentation are distributed under the MIT license.