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From Svetlomir Kasabov <skasa...@smail.inf.fh-brs.de>
Subject Sequence / Temporal Learning using Mahout's classifier
Date Fri, 01 Jul 2011 10:26:05 GMT
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 past-window of 2 and future-window 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.













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