Greetings I have grouped data which are divided into actives and inactives. The features are two different types of normalized scores (0-1), where the higher the score the most probable is an observation to be an "active". My data look like this:
Group1: score1 = [0.56, 0.34, 0.42, 0.12, 0.08, 0.21, ...] score2 = [ y=[1,1,1,0,0,0, ...] Group2: score1 = [0 score2 = [ y=[1,1,1,1,1] ...... Group24: score1 = [0 score2 = [ y=[1,1,1,1,1] I searched in the documentation about treatment of grouped data, but the only thing I found was how do do cross-validation. My question is whether there is any special algorithm that creates random forests from these type of grouped data. thanks in advance Thomas -- ====================================================================== Thomas Evangelidis Research Specialist CEITEC - Central European Institute of Technology Masaryk University Kamenice 5/A35/1S081, 62500 Brno, Czech Republic email: tev...@pharm.uoa.gr teva...@gmail.com website: https://sites.google.com/site/thomasevangelidishomepage/
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