Classification week3 - decision trees

gistfile1.txt

step 1 start with empty tree
step 2 select a feature to split data
FOr each split of tree
  step3 if nothing more to, make predictions
  step4 ohter wise go to step 2 and continue recurse on this split
  
Feature split learning = decision stump learning

what better: split on credit or term

step 1: y hat = class of majority of data node
step 2: calculate classification error of predicting yhat for this data

2 stopping condition: when all data agree on 1 choice or when no more feature to split

threshold for continous inputs