I have Multivariate time series samples around 100,000. Each MTS is 4 dimensional and length of the MTS varies. Minimum length is 2960 and the maximum length is 3500. I want to classify the data into two classes a and b. before applying the classifiers to the data I want to extract features from it. I have checked few feature extraction techniques such as 1DSVD, 2Dsvd, PCA based.I am confused that which feature extraction technique best suits for this task as there is large no of samples and the length of MTS varies.Please guide me regarding the feature extraction technique and type of classifier that suits my task
multivariate time series feature extraction
machine learning;classification;data mining;feature extraction