Decision Trees: Non-linear regression or classification with very little computation
	• The idea is to divide up the input space into a disjoint set of regions and to use a very simple estimator of the output for each region – For regression, the predicted output is just the mean of the training data in that region. • But we could fit a linear function in each region – For classification the predicted class is just the most frequent class in the training data in that region. • We could estimate class probabilities by the frequencies in the training data in that region.