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The likelihood split criterion can be used to prune the tree.
Split criterion is Gini's diversity index; maximum number of splits is 4. 2.
Split criterion is Gini's diversity index; maximum number of splits is 4. Decision tree (medium).
Firstly, a split criterion is proposed for building cost-time sensitive decision trees, aiming at possibly reducing the intangible cost.
On the other hand, for ER-LBD and HSE information gain ratio was the optimal split criterion.
For the second method, a separate set was constructed wherein the year of the publication was the split criterion.
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The pruning can be done either by stopping the splitting process once some "goodness of split" criteria have failed to be met or when the tree is complete (i.e. when all data has been clustered), nodes and branches need to be pruned.
This criterion is more robust to noise than the split criteria of the classic decision trees.
Then, each split was run on the respective subset of data as represented by the preceding RP split criteria.
Among the variables included in the RPA, age was omitted from the split criteria according to the order of priority.
During RPA, free software (R version 2.6.2; rpart package version 3.1.39-1, http://www.r-project.org/) was used for the recursive decision tree creation with the split criteria of p < 0.01 in the log-rank test.
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