Challenge #127: US Grand Prix Lap 2 - Employee Retention

[RWvanLeeuwen]

It is clearly described how the models should be entered, however, no employee is awarded a predicted probability to leave above ~.35 so none of the records join (using 2019.2 here, so perhaps some changes were made within underlying R packages such as C5.0, cart, partykit?)

Anyways, I did what was expected in the challenge and I wasted a lot of time to figure out why my results are different

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[cgoodman3]

Getting in some last minute practice ahead of my grand prix prelims next week!

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[OllieClarke]

Couldn't get the same answer, then saw the posts mentioning versions which I'm confident is the reason...

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[Jonathan-Sherman]

Challenge 127 is done!

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[hanykowska]

As others using newer versions, I couldn't get the same results... Definitely spent too much time trying to fix that

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[T_Willins]

Had it built in under 10 minutes, but took a long time to figure out why I was getting no results >= .5.  Finally looked at other newer replies and found the need to revert Decision Tree to earlier version.

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[Laszlo_D]

I slightly reinterpreted the challenge. Because of tool version discrepancies I decided to use all the available predictive tools to see if I can get similar records with any of them. The answer is no. I created my own list of employees by unioning the result from all the predictive tools and keeping the ones which came out of more than one tool.

[KeithZ]

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My predictive tools aren't outputting >= 0.5 probability. Either are other solutions I've downloaded... probably the difference in Alteryx versions since this challenge is 1+ years old. I'll still chalk this up as a win?!

[mbogusz]

Hmmm... interesting that the newer version of the Decision Tree and/or Score tool aren't backwards compatible with the older versions.

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