How to predict time series in scikit-learn?

Question

Scikit-learn utilizes a very convenient approach based on fit and predict methods. I have time-series data in the format suited for fit

Answer 1

This might be what you're looking for, with regard to the exponentially weighted moving average:

import pandas, numpy
ewma = pandas.stats.moments.ewma
EMOV_n = ewma( ys, com=2 )

Here, com is a parameter that you can read about here. Then you can combine EMOV_n to Xs, using something like:

Xs = numpy.vstack((Xs,EMOV_n))

And then you can look at various linear models, here, and do something like:

from sklearn import linear_model
clf = linear_model.LinearRegression()
clf.fit ( Xs, ys )
print clf.coef_

Best of luck!