K Nearest Neighbor Edition to Guide Classification Tree Learning: Motivation and Experimental Results - Data Mining: Theory, Methodology, Techniques, and Applications - page 55

Fig. 1. Single classifier construction. Induction of a Classification Tree.

Fig. 2. Example of a Classification Tree

- after allowing a huge expansion of the tree, we could revise a splitting mode

in a node removing branches and leaves, and only maintaining the node.
This technique is known as ”postpruning”.

The works that have inspired a lot of successive papers in the task of the
decision trees are [3] and [23]. In our experiments, we use the well-known decision
tree induction algorithm, ID3 [23].

3The K -NN Classification Method

Asetofpairs( x 1 ,θ 1 ) , ( x 2 ,θ 2 ) ,..., ( x n ,θ n )isgiven,wherethe x i 's take values in

a metric space X upon which is defined a metric d and the θ i 's take values in the