Generally, it means either the customer 'churned/left' or 'stayed' with the company. That is the variable we are trying to predict using our models. The other columns/features are used to aid the model in trying to find if there is a pattern between them (features) and the 'Target' being 1 or 0. Some of the columns may be useful, less useful, or even not useful at all in making the predictions.
@Rorisang, thank you for your reply. I have been assuming for a while now what the target renspose categories meant. As you can see when you plot the distribution of this rensponse variable there is a class imbalance with these two target categories. I just wanted to hear from others what 0 and 1 represented. Thank you
Yes, that is spot on.
Generally, it means either the customer 'churned/left' or 'stayed' with the company. That is the variable we are trying to predict using our models. The other columns/features are used to aid the model in trying to find if there is a pattern between them (features) and the 'Target' being 1 or 0. Some of the columns may be useful, less useful, or even not useful at all in making the predictions.
Hope that helps.
@Rorisang, thank you for your reply. I have been assuming for a while now what the target renspose categories meant. As you can see when you plot the distribution of this rensponse variable there is a class imbalance with these two target categories. I just wanted to hear from others what 0 and 1 represented. Thank you
Hi. Yes, I also noticed the class imbalance.
Pleasure,
Just to clarify as I am also misunderstanding whether 0 mean active clients
We are predicting churn so my assumption is target = 1 means that the customer has churned
I think 0 = active members and 1 = not active/ churned