Applying weights to Random Forest Prediction

[PauloBrum]

Hi,

I set up a problem using the workflow suggested at Random Forest, Gradient Boosted Trees, and TreeEnsemble – KNIME Community Hub . I haven’t been able to assign weights to the classes that represent adequately the costs of false positives, though.

For example, let’s say that the cost of a false positive is 4x the value of a true positive. How can I set up the workflow to take that into account? What I have been doing so far is a lot of trial-and-error in Excel to approximate the best cutoff value (e.g., accepting only the cases in which the class attributed to the item has a prediction value >.8), but I would like to do it in a more rigorous way.

Thanks!

[Mpattadkal]

Please have a look at this threads

I am doing a binomial classification. How can I put more weightage on a particular class?

I am doing a binomial classification(frauds & non frauds). How can I put more weightage on a particular class? I want to put more weightage on frauds so that I can capture more frauds compared to non frauds. How to do this, please help.

Let me know if the discussion here solves your query.

Thank you!