Für jede Dimension (Aggregate):

• Mittelwert
• Standardabweichung
• Skewness, Kurtosis, höhere Momente
• Maxima, Minima

Zeitreihensicht:

• Crosscorrelation zwischen Dimensionen und Autokorrelation
• Ordnung AR/MA, Parameter

Modellparameter

http://stats.stackexchange.com/questions/50807/features-for-time-series-classification http://nips.cc/Conferences/2012/Program/event.php?ID=3217 http://robjhyndman.com/hyndsight/tscharacteristics/

http://stats.stackexchange.com/questions/3238/time-series-clustering-in-r

• SVD: Problem bei verschieden langen Zeitreihen
• Vorschläge:
  • Auffüllen durch resamplen vergangener Werte
  • http://videolectures.net/mlss09us_candes_mccota/

http://stats.stackexchange.com/questions/1268/svd-dimensionality-reduction-for-time-series-of-different-length?rq=1

http://stats.stackexchange.com/questions/51475/series-dimensionality-reduction-for-classification-input?rq=1 http://stats.stackexchange.com/questions/9475/time-series-clustering/19042#19042

http://stats.stackexchange.com/questions/51475/series-dimensionality-reduction-for-classification-input?rq=1 http://stats.stackexchange.com/questions/39007/clustering-time-series-with-wavelets-in-r?rq=1

KNN + Dynamic Time Warping. http://stats.stackexchange.com/questions/66027/time-series-classification-very-poor-results?rq=1