Which machine learning model is best for this scenario?

classification
machine_learning
random_forest
python

#1

I have 60k to 70k records and 26 features like User_ID, Age, Salary, City(100 categories), Emp_Status(4 categories), Day of week, Time and Channel.
Target variable is Channel(5 categories)
Can any one tell me which model is best for this Use Case.
If I am using random forest then how i am going to handle city and target variable (Channel)
Thanks In Advance


#2

Multinominal regression, SVM, NN to an extent, discriminant analysis.

Some of these methods can be used for such a scenario where target is > 2 classification.

To an extent even Chaid can be used based on expected results.