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Error: Model Comparison: Tool #3: Error in names(scores) <- paste(score.field, "_", y.leve

AngelaLilan
7 - Meteor

Hi, I am Angela. I have been working on developing a logistic regression model and using the model comparison tool to compare models. I have been troubled by errors in the model comparison tool. I have tried to change the variables and punctuations but it doesn't help to solve the errors.

The error: Model Comparison: Tool #3: Error in names(scores) <- paste(score.field, "_", y.levels, sep = "") :

Any help would be appreciated!

Please find attached the workflow and input file. Thanks.

32 REPLIES 32
apathetichell
18 - Pollux

Does this version work for you with the original dependent variable? This is working on my system. note - I changed all of the field names to have "."s instead of spaces and there is still a non-fatal flag thrown by the linear model.

apathetichell
18 - Pollux

 

2021-06-08 (1).png

2021-06-08.png

  

And here's the version of the new dependent variable - I left some notes on the canvas explaining some of things I did and why.

AngelaLilan
7 - Meteor

Thank you very much for your help.

 

But what do you mean by adding a new version of the same tool when using a model to fix an error on the canvas?

 

Following that, I have added a decision tree, another model comparison and lift chart to the workflow. 
But the same errors show up again 

Error: Decision Tree (35): Decision Tree: The R.exe exit code (1) indicated an error.

 

A new error showed up too. It leads to the lift chart not showing any result. 

Error: Decision Tree (35): Decision Tree: Error in relevel.factor(actualValues, ref = ref) : 

 

May I know how can I fix it and why? 

Thanks. 

apathetichell
18 - Pollux

adding a decision tree to it gave me an error because it wanted a complexity parameter. I added one and got the following:

2021-06-08 (2).png

2021-06-08 (3).png

2021-06-08 (4).png

2021-06-08 (5).png

    

AngelaLilan
7 - Meteor

Ok thanks. It is fixed. 

 

But for the 'score', it received a warning:

Warning: Score (17): Not all records were scored due to missing values in the predictor fields or unknown categorical values. 

 

May I know what happened?

 

Thanksss.

apathetichell
18 - Pollux

The tree tool really doesn't like  "West" in the Region category. I had the hyperparameters minimum value set to 20 and with:

Region Count
Central 272
East 127
Midlands 358
North 277
North-East 84
North-West 189
South 60
South-East 138
South-West 92
West 36

 

in your total data set - the training version didn't have over 20 instances so it didn't want to create any splits with West as a qualifier. At least - that's how I'm reading it.

AngelaLilan
7 - Meteor

So should I change the number for  'The minimum number of records needed to allow for a split'? Or what should I change?

 

I have tried to change 'The minimum number of records needed to allow for a split'? Or what should I change? ranges from 5-15 but none of it seems to solve the error.

 

Thanks.

apathetichell
18 - Pollux

I set the minimum number of records to 2 and lowered the complexity and it didn't flag any errors and seems to allocate 1143 records to the tree. I can't promise that was the source of the error - but it makes logical sense to me that it wouldn't want to score on a missing category.

2021-06-08 (6).png

2021-06-08 (7).png

  

AngelaLilan
7 - Meteor

Ok thanks.

But I have tried to run the workflow again today but it said :

Error: R (36): AlteryxProcessManager::Start: Timed out in ConnectNamedPipe after 5000 milliseconds 

 

for all the models. May I know what is going on?

 

Thanks.

apathetichell
18 - Pollux

Hi!

 

I have no idea - as I haven't seen that error - maybe someone from technical support can help?  Here's what some forum people reported on that issue:

https://community.alteryx.com/t5/Alteryx-Designer-Discussions/Error-in-ConnectNamedPipe/td-p/81262/p...

 

there's also the disconnect the R tool and then reconnect it option. So most Alteryx tools just kind of do their things and exist in a relative vacuum - but that's not true for R, Python, R-based tools, and a few others. So they get more hiccups.

 

maybe @CristonS  can help?

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