Self-Organising Map (SOM) with Principle Component Analysis (PCA)
4 Ansichten (letzte 30 Tage)
Ältere Kommentare anzeigen
naghmeh moradpoor
am 19 Jun. 2017
Beantwortet: Greg Heath
am 22 Jun. 2017
Dear all, I want to use Self-Organising Map (SOM) [unsupervised machine learning] for my anomaly detection problem. But before that I would like to find suitable input features that cause the best results. I have total of eight input features. Would you use Principle Component Analysis (PCA) to find best features? What would you do? Regards, Naghmeh
0 Kommentare
Akzeptierte Antwort
Greg Heath
am 22 Jun. 2017
It is not clear if you have a well defined output.
If so, it IS NOT the variation of the inputs that are paramount.
It IS the variation of the outputs w.r.t. the inputs.
Check out principal COORDINATE analysis (very different from principal COMPONENT analysis!)
Hope that helps.
Thank you for formally accepting my answer
Greg
0 Kommentare
Weitere Antworten (0)
Siehe auch
Kategorien
Mehr zu Dimensionality Reduction and Feature Extraction finden Sie in Help Center und File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!