BookmarkSubscribeRSS Feed
☑ This topic is solved. Need further help from the community? Please sign in and ask a new question.
Ronein
Onyx | Level 15

Hello
I build a credit risk model on 100,000 customers.

I split the data into train 70% and test 30% and built the model on train data. 

Then ,the results are Gini 79% on train data.

 

I calculated PD based on model coefficients on out of time data.

Gini of Out of time data is 80%

My question- is this difference of 1%  between out of time and train  is okay or mention a problem ?

What other tests would you do in such case?

I checked PSI for all predictors   and it show high stability  for each of predictors

 

1 ACCEPTED SOLUTION

Accepted Solutions
PaigeMiller
Diamond | Level 26

@Ronein wrote:
No. Here is out of time vs train data and other question was train data vs test data

Changing a few of the words doesn't change the meaning of the question. Your two posts have the same meaning, and likely the same answer.

--
Paige Miller

View solution in original post

4 REPLIES 4
PaigeMiller
Diamond | Level 26

You are asking the same question as https://communities.sas.com/t5/SAS-Data-Science/Gini-credit-risk-model/m-p/954433#M10965

Please do not double post questions.

 

PS: There is an answer at your other thread.

--
Paige Miller
Ronein
Onyx | Level 15
No. Here is out of time vs train data and other question was train data vs test data
PaigeMiller
Diamond | Level 26

@Ronein wrote:
No. Here is out of time vs train data and other question was train data vs test data

Changing a few of the words doesn't change the meaning of the question. Your two posts have the same meaning, and likely the same answer.

--
Paige Miller
Ronein
Onyx | Level 15
In this question I ask about train data vs out of time data ( model develop on data from June 2021 and out of time data is for example June 2023). In previous post my question was about train data ( 70%) vs test data (30%) ...

hackathon24-white-horiz.png

The 2025 SAS Hackathon Kicks Off on June 11!

Watch the live Hackathon Kickoff to get all the essential information about the SAS Hackathon—including how to join, how to participate, and expert tips for success.

YouTube LinkedIn

How to choose a machine learning algorithm

Use this tutorial as a handy guide to weigh the pros and cons of these commonly used machine learning algorithms.

Find more tutorials on the SAS Users YouTube channel.

Discussion stats
  • 4 replies
  • 2826 views
  • 1 like
  • 2 in conversation