BookmarkSubscribeRSS Feed
🔒 This topic is solved and locked. Need further help from the community? Please sign in and ask a new question.
ravi4
Calcite | Level 5
Hello,
I'd be grateful to have some clarity regarding these two variables that are created after running a Decision Tree to predict a binary target,-
1) label "Validated:Target_B=1" with Variable name "V_TARGET_B1" and,
2)label "Predicted:Target_B=1" with Variable name "P_TARGET_B1"
There seems to be a small difference between the above two p values mostly corresponding to the third digit after the decimal. What is the difference between these variables. I find them in both the training and the validation datasets of the output.
Thanks in advance,
Ravi.
1 ACCEPTED SOLUTION

Accepted Solutions
WendyCzika
SAS Employee

The V_ variables are the predictions based on the validation data - so the proportion of validation obs. in the leaf with target=B1 for whatever leaf the current observation is in.  The P_ is the same thing but using the training partition, and the actual prediction is based on this value.

View solution in original post

1 REPLY 1
WendyCzika
SAS Employee

The V_ variables are the predictions based on the validation data - so the proportion of validation obs. in the leaf with target=B1 for whatever leaf the current observation is in.  The P_ is the same thing but using the training partition, and the actual prediction is based on this value.

sas-innovate-2024.png

Available on demand!

Missed SAS Innovate Las Vegas? Watch all the action for free! View the keynotes, general sessions and 22 breakouts on demand.

 

Register now!

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
  • 1 reply
  • 853 views
  • 1 like
  • 2 in conversation