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https://issues.apache.org/jira/browse/MAHOUT-1525?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13980395#comment-13980395
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Suneel Marthi commented on MAHOUT-1525:
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You shouldn't be using 0.7, 0.7 has long been retired and is unsupported. 
Please upgrade to 0.9 or work off of trunk.

> train/validateAdaptiveLogistic
> ------------------------------
>
>                 Key: MAHOUT-1525
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-1525
>             Project: Mahout
>          Issue Type: Question
>          Components: Classification
>    Affects Versions: 0.7
>            Reporter: Richard Scharrer
>              Labels: adaptiveLogisticRegression,, newbie
>
> Hi,
> I tried to use train- and validateAdaptiveLogistic on my data which is like:
> category, id, var1, var2, ...var72 (all numeric)
> I used the following settings:
> mahout trainAdaptiveLogistic --input resource/trainingData \
> --output ./model \
> --target category --categories 9 \
> --predictors a0 a1 a2 a3 a4 a5 a6 a7 a8 a9 a10 a11 .....
> --types numeric \
> --passes 100 \
> --showperf \
> mahout validateAdaptiveLogistic --input resource/testData --model model 
> --confusion --defaultCategory none
> The output of validateAdaptiveLogistic is:
> Log-likelihood:Min=-5.54, Max=-0.04, Mean=-1.58, Median=-1.33
> =======================================================
> Confusion Matrix
> -------------------------------------------------------
> a     b       d       e       f       g       h       i       <--Classified as
> 14    0       0       0       0       0       0       0        |  14          
> a     = projekt
> 0     18      0       0       0       0       0       0        |  18          
> b     = news/aktuelles/presse
> 0     0       24      0       0       0       0       0        |  24          
> d     = lehrveranstaltung
> 0     0       0       19      0       0       0       0        |  19          
> e     = publikation
> 0     0       0       0       20      0       0       0        |  20          
> f     = event
> 0     0       0       0       0       14      0       0        |  14          
> g     = mitarbeiter/person
> 0     0       0       0       0       0       44      0        |  44          
> h     = übersicht
> 0     0       0       0       0       0       0       13       |  13          
> i     = institut
> (in case you were wondering, the categories a in german)
> My problem is that this is impossible. I always get a perfect classification 
> even with just a little amount of training data. It doesnt even matter how 
> many features I use I tried it with all 72 and with only one. Am I missing 
> something?
> Regards,
> Richard



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