Help with the list of must know Classification algorithms




I am a new to machine learning and currently exploring about classifications algorithms. I have looked at these algorithms:

  • Logistics Regression
  • SVM
  • Decision Tree
  • Random Forest

Should I go for other algorithms also if yes, please help me with the list.

One more question, can you help me that how should I decide which algorithm will work better comapare to other in any scenario?



In my experience random forest is the most appropriate and easiest to use model in most cases.

However, if interpretability is required then logistic regression or classification trees are better.

If one needs control over how each feature is treated then GAMs are useful (Generalized Additive Models).

If there are too many features and overfitting is an issue then ridge regression is good (suitably modified for classification).

A good way to decide which model will work better is cross validation, or try it out on a separately held out validation set of data