监督学习_决策树
Supervised Learning = Approximation--signal exist
Unsupervised Learning = Description-- try to find a signal
density estimation about pixel-- so it is a question about statistics
reinforcement learning is described as learning from delayed reward
generalization -- inductive bias
induction -- from examples to more general rules
deduction -- opposite
the difference between classification and regression: if the output is discrete then it is the classification
XOR is complicated because the different lines have 2^n then the outcomes have 2^2^n. This is tricky so to understand this, you could try to understand when n=1 and n=2. Then you should be clear.
When the attributes are continuing then it is possible and reasonable to repeat the attribute in the same branch since we may want to know more clearly about the attributes.