I am new to the field of machine learning. I have just recently learnt Decision Trees and started solving Titanic Survival problem from Kaggle Competition. I understood the algorithm behind decision trees and how it actually works but I can't really match it with how python functions work this way. Say what exactly fit method does?
Well correct me if my concept is wrong. I think that looking at the train set i can build a model on "if a passenger survived or not" . Then I split the model into train set and test set and then the fit method (x_train, x_test) (this is what i think it works) actually tries to find the connection between x_train and y_train. I BUILT using my Train dataset and then tries to predict my test set. Say if i change my model, the fit method will try again to find the connection between my x_train and y_train using my new model. (Sorry for some terms as I am a self-learner. I don't really have the grasp of machine learning terms)
It will be of great help if you could suggest some simple data science problems which can be solved using Decision trees(besides Iris dataset)