Self-Organising Map (SOM) with Principle Component Analysis (PCA)
4 visualizzazioni (ultimi 30 giorni)
Mostra commenti meno recenti
naghmeh moradpoor
il 19 Giu 2017
Risposto: Greg Heath
il 22 Giu 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 Commenti
Risposta accettata
Greg Heath
il 22 Giu 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 Commenti
Più risposte (0)
Vedere anche
Categorie
Scopri di più su Dimensionality Reduction and Feature Extraction in Help Center e File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!