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Also it measures the performance of the algorithms on training sets of a size signiﬁcantly smaller than the whole dataset. 3 DataMining 43 The Resampled Paired t Test The resampled paired t test is the most popular in machine learning. Usually, there are a series of 30 trials in the test. In each trial, the available sample S is randomly divided into a training set R (it is typically two thirds of the data) and a test set T . The algorithms A and B are both trained (i) (i) on R and the resulting classiﬁers are tested on T .
Connect the root node of tT to Subtreei with an edge that is labelled as vi END FOR END IF RETURN TreePruning (S,T ,y) TreePruning (S,T ,y) Where: S - Training Set y - Target Feature T - The tree to be pruned DO Select a node t in T such that pruning it maximally improve some evaluation criteria IF t = Ø THEN T = pruned(T, t) UNTIL t = Ø RETURN T Fig. 1 Top-Down Algorithmic Framework for Decision Trees Induction. 1 Overview An important problem in the KDD process is the development of eﬃcient indicators for assessing the quality of the analysis results.
Since the absolute size is not meaningful, it should be normalized by calculating the proportional area. 7) The F-measure can have values between 0 to 1. 2 are identical and it obtains its lowest value when the two sets are mutually exclusive. Note that each point on the precision-recall curve may have a diﬀerent F-measure. Furthermore, diﬀerent classiﬁers have diﬀerent precision-recall graphs. November 7, 2007 13:10 WSPC/Book Trim Size for 9in x 6in Evaluation of Classification Trees Fig. 5 DataMining 27 A graphic explanation of the F-measure.