2015-04-22 11:20:44 -0600 | received badge | ● Enthusiast |
2015-04-11 14:48:33 -0600 | asked a question | How to train DTree until it completely separates data? I need to train a decision tree that completely fits my data. I _want_ it to over-fit. Thus, I don't want it to be pruned, and I want it to grow the tree until every leaf has samples with only one label. Mine is a classification task, with two labels. Here are the params I used: And here is how I'm training: Unfortunately, for some benchmarks, the tree that is trained does not classify all training points correctly. How can I enforce this? |
2015-03-02 21:45:38 -0600 | asked a question | Bad argument error for default value of mask in CvDTree::train() I have the following code: But when I run it, I get the following error: This is strange, because the value I've given for mask (Mat()) is the default value, as per the docs. What's going on? |