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From Svetlomir Kasabov <>
Subject Sequence / Temporal Learning using Mahout's classifier
Date Fri, 01 Jul 2011 10:26:05 GMT

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

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.


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