Machine Learning - Decision Tree
Machine Learning - Decision Tree I am still not sure about the Decision Tree's pruning feature. That is: What exactly happens in pruning in DT? Do rows (observations) get deleted OR Do columns (features / x-variables / independent variables) get deleted? For instance, if there are 1000 rows and 10 features in my dataset and I build a decision tree model (using all 10 features), then after pruning, Do 1000 rows reduce to (1000-n) observations OR do 10 features reduce to (10-n) features OR Both Is there any way I can see what happens what exactly gets pruned from my observations? Any way I can compare the original vs Pruned model? Thanks. Neither. Pruning reduces the depth of the tree – vahndi Jul 1 at 3:22 By clicking "Post Your Answer", you acknowledge that yo...