SimuChemPC (version 1.3)

trainChemPC: trainChemPC

Description

Apply Gaussian Process Regression to learn the model.

Usage

trainChemPC(xTrain, yTrain)

Arguments

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.

Value

It returns a vector that holds calculated loghyper parameters.

Details

This function performs training step of GP or EI by finding loghyper parameters.

References

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/

Examples

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)