Test your own music style
Please note that this demo can provide only a coarse assignment of your affinities to the predefined music styles. By using more variables (in this case, responses from the questionnaire) to generate the model, the SOM will be more selective, allowing more sophisticated prediction.
Data source and acknowledgement
The online PARSHIP dating service provided approximately 120,000 anonymous records which were used for the initial data set. The records primarily contained 24 attributes for describing the hobbies and interests of European members over 18 years as well as their social demographic variables.
PARSHIP regularly validates their matching algorithms to provide their members with the best possible partner suggestions. You can find the PARSHIP dating service here.
Variables were standardized and scaled according to defaults by Viscovery. Correlation compensation was automatically applied for the variables. The Age attribute was transformed sigmoidally.
The values of the Education attribute were grouped into an ordinal variable with 3 levels. Active and passive hobbies were combined independently for each variable.
The presented model was calculated only from complete records that contained no missing values.
The resulting self-organizing map with 500 microclusters (“nodes”) was created form the final data set with Viscovery SOMine using standard settings, “Normal” training schedule, and a “Tension” of 0.6.
To generate the displayed SOM from an initially larger number of attributes, only those attributes contributing to the ordering of music preferences were chosen and prioritized iteratively until the music preferences – which were not prioritized – were differentiable. The final priorities for the attributes were as follows: 1.0 for Age, 0.9 for Education, 0.6 for Gender, 0.7 for Theater, Literature, and Art, 0.6 for Film/Video and for Dance.
For the online classification, respondent records were grouped into approximately 400 clusters to ensure sufficient granularity to differentiate the entire set.