Hello,
I plan performing sequence/temporal learning using one of Mahout's
classifier (probably OnlineLogisticRegression, since I need
probabilities as outcome).
For example, we have this data:
t X Y

T1 xT1 Y1
T2 xT2 Y2
T3 xT3 Y3
T4 xT4 Y4
where, for example xT1 is the value of X in time T1 and we know that Y
depends conditionaly on X (this means that Y is target variable and Y is
a predictor).
If we assume, that we have pastwindow of 2 and futurewindow of 1, we
can construct our training examples this way (using sliding windows)
Feature1 Feature2 TargetVariable

xT1 xT2 Y3
xT2 xT3 Y4
...
(this learning model is based on
http://neuroph.sourceforge.net/tutorials/ChickenPricePredictionTutorial.htm)
So we get a logistic regression model for with number of features = past
window size. But what if Y depends on more than one predictor (for
example Z)? How can we map X and Z to one time unit  should we extract
also two more features for Z, analog to X)?
The second question is  what if I have size of future window >=2 ? The
problem is, that I can have only one target variable in a logistic
regression, so I can't train a model with such window size. Is that correct?
Thanks and sorry for the long post.
Svetlomir.
