When conducting a prediction, what is the order of the two categories, if I am using binary0= not return, 1 =will return, of the outcome/target variable? Is the order always 0 then 1?
Are the coefficients predicting 1 first, a student will return, or predicting 0, whether a student will not return?
Additionally, are the coefficients listed in under Logistic Regression the Odds Ratio?
The logistic regression coefficients in DSS are the log of the odds ratio, not just the odds ratio. If the binary target is encoded as 0/1, then DSS will predict the probability that a given observation belongs to the 1 (or positive) class.
If you are ever unsure what DSS is choosing as the 'positive' class, you can got into the model analysis, select your model, go down to Performance, click on Confusion Matrix, and check the sidebar discussion in the blue box. Attached is a screenshot of the sidebar for the DSS Academy project looking at t-shirt sales predictions with the target set to high_revenue.
Thank you @MaureenP. I appreciate your explanation. I have not heard of the Log of the Odds ratio before. I presume that this number is similar, in that a variables log of the Odds Ration if positive, is the % of the increase in the likelihood of 1 or True and a negative is the % decrease in the likelihood of 1 or True.
In the attached example, does it read that there is a 60% increased likelihood in retention for that variable and a 30% decreased likelihood in retention for the next variable.