on 09-01-2016 6:05 AM
Hi All,
Is there any sample to show complete work flow (full life cycle PA Implementation) which explains ,
1. Data pre-processing (using correlation matrix, cleanup method)
2. Building the model (Decision Tree or any classification model)
3. Measure performance of model (PSME, AUC-Area under curve and Confusion Matrix)
Regards,
Naveen
Hi Naveen, could you please let us know what is missing in our answers? In case nothing is missing, could you please set the thread as "Answered"? Thanks in advance, Antoine
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Hi Naveen,
Adding to Paul's comment... that error you see is on the partition node and is very likely due to unsupported types in your dataset. Please refer section "The following are the supported CSTYPE" in release restriciton note: https://launchpad.support.sap.com/#/notes/0002295127 for details.
Also, I am not sure if I understand what system date change are you referring to there and its objective.
Regards,
Jayant
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Few additional things:
- Jayant covered an end to end scenario in his blog here:
- This will also be presented in an ASUG webinar planned for October 12: ASUG.com - Events
- it's a webinar series where we cover a scenario end to end.
- in Jayant's blog you can notice we display AUC indicators, alongside with the Prediction Confidence (KR) and the Predictive Power (KI)
Thanks & regards,
Antoine
Hi Naveen,
You can use the Model Statistics node in Expert mode to evaluate any two-class classification model (AUC, S(KS), Gain%, Lift%, etc.) or regression model (R2, L1, L2, Linf, Error Mean, Error Std Dev, etc.). The component computes different KPIs (as listed in brackerts) from the results of training that can be fed into Model Compare node to automatically pick the best model in a parallel chain.
Blog post referred by Antoine has more details.
Regards,
Jayant
PS: You can have a look at 's blog for extensions in R for use in Expert mode.
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