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From "Dmitri O.Kondratiev" <>
Subject Re: Function approximation in Mahout?
Date Wed, 21 Apr 2010 22:08:21 GMT
I have 165000 observations. Each observation is 180 component vector.
One component in this vector is an integer in range from 0 to 200.

Every vector is constructed from readings of 180 sensors. Sensors fail
unpredictably, so some vector components may be undefined. On average
40% - 60% of random vector components are undefined in every vector.

I am trying to find an approximation function for each component of
these vectors.

What other methods for prediction with incomplete data can be used for
a task I just described?

>From	Ted Dunning <>
>Subject	Re: Function approximation in Mahout?
>Date	Wed, 21 Apr 2010 14:34:58 GMT


>Mahout does not have a lot of regression capabilities at this time, other

>than various forms of binomial regression (SVM, logistic regression,
>decision forests) but other forms of regression are relatively lacking.
>Commons math has some capabilities, but not in a particularly scalable form.
>What size is your problem?
>On Tue, Apr 20, 2010 at 2:07 PM, Dmitri O.Kondratiev <>wrote:
>> Hello,
>> Does Mahout support any function approximation frameworks, such as greedy
>> function approximation with gradient boosting (TreeNet)?
>> Thanks!

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