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









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