GLM Shows Significance But Decision Tree Unable to Predict?

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VikR
Posts: 13
Joined: Thu Oct 13, 2011 10:34 pm

GLM Shows Significance But Decision Tree Unable to Predict?

Postby VikR » Fri Sep 28, 2012 7:58 pm

I'm trying to predict brand preference based on a number of attributes.

General Linear Model shows that all but one attribute has a significance of < 0.05, so one might expect I'd have a good ability to predict brand selection.

But running a Decision Tree shows that the correct brand is predicted only 25.7% of the the time.

What am I missing?

Thanks very much in advance to all for any info!

Code: Select all

* Generalized Linear Models.
GENLIN BRAND_ID WITH Attribute_1 Attribute_2 Attribute_3 Attribute_4 Attribute_5 Attribute_6 
    Attribute_7 Attribute_8 Attribute_9
  /MODEL Attribute_1 Attribute_2 Attribute_3 Attribute_4 Attribute_5 Attribute_6 Attribute_7 
    Attribute_8 Attribute_9 INTERCEPT=YES
 DISTRIBUTION=POISSON LINK=LOG
  /CRITERIA METHOD=FISHER(1) SCALE=1 COVB=MODEL MAXITERATIONS=100 MAXSTEPHALVING=5 
    PCONVERGE=1E-006(ABSOLUTE) SINGULAR=1E-012 ANALYSISTYPE=3(WALD) CILEVEL=95 CITYPE=WALD 
    LIKELIHOOD=FULL
  /MISSING CLASSMISSING=EXCLUDE
  /PRINT CPS DESCRIPTIVES MODELINFO FIT SUMMARY SOLUTION.


* Decision Tree.
TREE BRAND_ID [n] BY Attribute_1 [s] Attribute_2 [s] Attribute_3 [s] Attribute_4 [s] Attribute_5 
    [s] Attribute_6 [s] Attribute_7 [s] Attribute_8 [s] Attribute_9 [s] 
  /TREE DISPLAY=TOPDOWN NODES=STATISTICS BRANCHSTATISTICS=YES NODEDEFS=YES SCALE=AUTO
  /DEPCATEGORIES USEVALUES=[VALID]
  /PRINT MODELSUMMARY CLASSIFICATION RISK
  /METHOD TYPE=CRT MAXSURROGATES=AUTO PRUNE=SE(1)
  /GROWTHLIMIT MAXDEPTH=AUTO MINPARENTSIZE=100 MINCHILDSIZE=50
  /VALIDATION TYPE=NONE OUTPUT=BOTHSAMPLES
  /CRT IMPURITY=GINI MINIMPROVEMENT=0.0001
  /COSTS EQUAL
  /PRIORS FROMDATA ADJUST=NO.

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