Calculation of Information Entropy in Data Mining with Decision Tree
Sun Weihua · Jisuanji gongcheng · 2001
We introduce the algorithm of how to build a decision tree by the comparison of information value or entropy and how to deal with something special, e.g. how to handle high-branching attributes, numeric attributes, missing values and how to prune. Finally, we show some source code of some modules in our implementation of this algorithm and give some introduction about the research of data mining at home and abroad.