RandomTree is a Weka specific reference to a single tree of a RandomForest.
Mar 10, noPruning – Pruning means to automatically cut back on a leaf node that does not contain much information. This keeps the decision tree simple and easy to interpret. numFolds – The specified number of folds of data will be used for pruning the decision tree. The rest will be used for growing the bushfelling.barted Reading Time: 10 mins. Jul 20, The unpruned trees are larger.
What happens is that basically the tree is created according to the implemented algorithm and if pruning is enabled, an additional step looks at what nodes/branches can be removed without affecting the performance too much. The idea behind pruning is that, apart from making the tree easier to understand, you reduce the risk of overfitting to the training.
Sep 22, Data Mining with Weka: online course from the University of WaikatoClass 3 - Lesson 5: Pruning decision treesbushfelling.bar (PDF): https://.
Sep 25, RandomTree is a Weka specific reference to a single tree of a RandomForest. This equals random feature selection at each node in just one tree on the entire data set. Reduced-Error Pruning Decision Tree (REPTree) REPTree (Reduced-Error Pruning) is another algorithm that is specific to Weka.
The concept of decision tree learning must be extended in several ways to be useful in practice.
It is a fast decision tree learner that is optimised for simplicity and bushfelling.bars: 1. Aug 08, To get around this problem, having constructed a decision tree, decision tree algorithms then automatically prune it back.
You don’t see any of this, it just happens when you start the algorithm in Weka.5/5(56).