Predict the best time of call
You might actually encounter problems if you model this as a regression problem without a suitable transformation. For instance, we know that most calls are probably answered during daytime and less during night time and early morning. A linear regression would have difficulty because the relationship is likely curvilinear, not linear. For the same reason, treating this as a classification task with logistic regression would also be problematic. 

As suggested by other respondents, reclassifying your data into time periods will help, and I'd suggest you try something like a decision tree or random forest first. 

That all said, this might be a case for simple descriptive statistics. If you plot the proportion answered calls by time of day (split by city or any other demographic), is there a clear best time?  If so, why complicate things with a model?