[MAHOUT-1525] train/validateAdaptiveLogistic

• Type: Question
• Status: Closed
• Priority: Major
• Resolution: Fixed
• Affects Version/s: 0.7, 0.8, 0.9
• Fix Version/s: 0.10.0
• Labels: adaptiveLogisticRegression, newbie
• Assignee: Unassigned
• Reporter: Richard Scharrer
• Created: 24/Apr/14 18:23
• Updated: 31/Jan/24 22:12
• Resolved: 26/Apr/14 19:58

Description

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