Hi
I’m developing a model using train and test data set partitions and would like to score the model on a new dataset that doesn’t have values of the independent variable yet. This is because the event hasn’t happen yet and I’d like to have the scores represent probability of the classification displayed.
For example, let’s say I am developing a marketing response model and have a list of all of the past marketing campaign responders and non-responders. I also have a bunch of variables I use as predictors to predict their probability to respond.
Now that I have the model developed I have another dataset of customers and would like to get each customers probability to respond to a new campaign.
The old campaign model dataset would look something like this:
Row_ID Predicor 1 Predictor 2 Actual_Campaign_response Campaign_Response_Probability
1 23 34 YES 0.854
2 39 45 YES 0.745
3 15 12 NO 0.241
Here’s what the new customer dataset ready to be used for the new campaign would look like:
Row_ID Predicor 1 Predictor 2 Predict_Campaign_response Campaign_Response_Probability
1 56 23
2 30 56
3 11 36
Now, I’d like to use the model developed on the onld campaign dataset and apply it to predictors 1 and 2 values in the new customer dataset and populate the predicted campaign response and campaign response probabilities using the old model and new values of the predictors.
Is there a node that would do this?
If so how would one use it?
Thanks a lot!