this might be simple but I need to know how to choose a best algorithm based on a scenario.
I have a dataset. The target class is, let's say
color attribute can have upto 5 values (red, yellow, blue, green, pink)
So I have:
1.) 1 target class -
2.) Multiple values for that target class - (red, yellow, blue, green, pink)
As this is a labelled dataset with known classes, I can use a
Supervised Learning Algorithm
But I don't know which algorithm would be the best. It should be a
multi-class classigication? Or
multi-labeled ? Can someone help me to find the best algorithm?
note: I know choosing an algorithm depends on many factors (such as its acuracy), but at a glance, what type of algorithms should I try?