Details of Lecture 27, ECE662 Spring 2010
April 24, 2010
In Lecture 27, we discussed decision trees. We began with an example of decision tree where the first query does not decrease the impurity of the data (the country question as part of deciding if a person is married or not). We then gave another example of decision tree (the fruit identification tree) where each of the queries decreases the impurity of the data. That latter example featured several categories (the fruits), while the former featured only two categories ("married" and "not married"). We mentioned that decision trees should be build in such a way as to decrease the "impurity" of the data, and concluded by defining different measures of data impurity.
Recall that next Thursday's lecture (4-29-10) is canceled, and that there is a make up class Friday (4-30-10), 1:30-2:30 in EE117.
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