Sorry, the previous email was incomplete. Below is how the grouped data look like:
Group1: score1 = [0.56, 0.34, 0.42, 0.12, 0.08, 0.21, ...] score2 = [0.34, 0.27, 0.24, 0.05, 0.13, 0,14, ...] y=[1,1,1,0,0,0, ...] # 1 indicates "active" and 0 "inactive" Group2: score1 = [0.34, 0.38, 0.48, 0.18, 0.12, 0.19, ...] score2 = [0.28, 0.41, 0.34, 0.13, 0.09, 0,1, ...] y=[1,1,1,0,0,0, ...] # 1 indicates "active" and 0 "inactive" ...... Group24: score1 = [0.67, 0.54, 0.59, 0.23, 0.24, 0.08, ...] score2 = [0.41, 0.31, 0.28, 0.23, 0.18, 0,22, ...] y=[1,1,1,0,0,0, ...] # 1 indicates "active" and 0 "inactive" On 1 December 2016 at 14:01, Thomas Evangelidis <teva...@gmail.com> wrote: > 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/ > > -- ====================================================================== 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/
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn