Community Spring Cleaning week is here! Join your fellow Maveryx in digging through your old posts and marking comments on them as solved. Learn more here!

Alteryx Designer Desktop Discussions

Find answers, ask questions, and share expertise about Alteryx Designer Desktop and Intelligence Suite.
SOLVED

Score tool

Fernström
6 - Meteoroid

Hi,

I have encountered a problem when using the score tool in combination with the boosted model.

 

After running the model through the score tool, I use the multi-field binning tool to get 10 score groups. However, when linking the target group to the binned scoring groups I can see that I get a higher concentration of the target in groups associated with a lower probability and vice versa.

 

When doing the exact same procedure using the logistic regression I get the expected result with higher concentration in the top scoring groups.

 

Below are tables for boosted and logistic, showing the tiles, max and min probability for each tile and the counts for my target "Kund" in the evaluation sample. I use the exact same scoring procedure.

 

For me it seems like the probability of target is actually the probability of not target when using the boosted model. Does anyone have an idea why I get this result?

 

Boosted    
X_Kund_Tile_Num Min_X_KundMax_X_KundCount
10Kund0.6166540125937370.703683675012687229
9Kund0.5998994118472230.616538099066424274
8Kund0.5851705470296210.599889418992929305
7Kund0.5698567492925720.584921578458874330
6Kund0.5527005626201640.569847550773193329
5Kund0.532109193718170.55252102221165361
4Kund0.499074921823790.532013523926153398
3Kund0.4351004700071770.498906496353244498
2Kund0.365537925403480.434932812596185638
1Kund0.1769420676579170.365379109142474998
     
     
Logistic    
X_Kund_Tile_Num Min_X_KundMax_X_KundCount
10Kund0.6108988359273190.729458226984427908
9Kund0.5721797350820820.610562695487317655
8Kund0.5383617008492240.572172160535576546
7Kund0.5065572334051560.538354010636627402
6Kund0.4769004371637320.505566504353257316
5Kund0.4490708903484960.476780988643294289
4Kund0.422922322907370.448520984912177277
3Kund0.3958859915844480.421955291607139321
2Kund0.3669054459876120.395807870615525319
1Kund0.302408176345360.366870729205422327
2 REPLIES 2
CristonS
Alteryx Alumni (Retired)

Hi @Fernström - this is due to changes in the underlying R package gbm() in the Boosted Model tool, where it now provides the probability for the first level of the target (when you choose the Bernoulli loss function for binary targets). We are aware of this issue, and are working to address it.

 

In the meantime, in the case of binomial outcome, there is actually no need to specify the specify the Bernoulli loss function since what it does by default results in the same loss function when there are only two outcomes.

Fernström
6 - Meteoroid

I see. Thanks a lot for the explanation!

Labels