"Value Series"

labrat

Hi all,

I am working on a project using RM, and i have a question about Multiple value series, let me explain.

Currently i am trying to predict whether a string of amino acids are an Epitope (E) or not (N).  The strings are all fixed at length 20, and there are several models of prediction, with varying accuracies. These models give out a string of scores on a sliding window across the protein.


EG
Sequence ABCDEF
Model1  1,2,3,4,5,6,7
Model2  3,5,2,4,5,6,9
Model3 ,6,2,2,3,1,7,6
label E


and i was wondering how i would go about combining these scoring models to put into an SVM.

EG:

ID,[MODEL1],[MODEL2],[MODEL3],label.
ID,[1,2,3,4,5,6,7],[3,5,2,4,5,6,9],[6,2,2,3,1,7,6],E

I hope that makes sense.

Stuart

PS:

The SVM i will be using will be the bog standard Xval-SVM from the wizard

land

Hi Stuart,
if I understand you correctly, you want to learn on the predictions of three different learning algorithms? If you want to do this, you could use the MetaLearning operator Stacking, where you put the SVM as first operator and an OperatorChain containing the three learning schemes producing your current models. This already should do the trick.

Greetings,
  Sebastian