Description Usage Arguments Details Value Author(s) References Examples
Apply Gaussian Process Regression to learn the model.
1 | trainChemPC(xTrain, yTrain)
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xTrain |
m * n martrix of train data. |
yTrain |
m * 1 matrix of target values consist of potencies, pIC50 or other measurements of compound affinities that are desired to be maximized. |
This function performs training step of GP or EI by finding loghyper parameters.
It returns a vector that holds calculated loghyper parameters.
Mohsen Ahmadi
1.
Predicting Potent Compounds via Model-Based Global Optimization, Journal of Chemical Information and Modeling, 2013, 53 (3), pp 553-559, M Ahmadi, M Vogt, P Iyer, J Bajorath, H Froehlich.
2.
Software MOE is used to calculate the numerical descriptors in data sets. Ref: http://www.chemcomp.com/MOE-Molecular_Operating_Environment.htm
3.
ChEMBL was the source of the compound data and potency annotations in data sets. Ref: https://www.ebi.ac.uk/chembl/
1 2 3 | x = as.data.frame(array(1:100, dim=c(20,5)))
y = as.matrix(as.numeric(array(1:20, dim=c(20,1))))
loghyper = trainChemPC(x, y)
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