R: Predictions for the external validation set and graph
graphe_3Sets
R Documentation
Predictions for the external validation set and graph
Description
Calulate the predicted values for the external validation set and trace the graph experimental values vs predicted values for training, test and external validation sets.
Multi linear regression between property and selected descriptors (lm object)
mydata
Dataframe containing names and values of response and descriptors
mynewdata
Dataframe containing property and selected descriptors values for the test set
mynewdata2
Dataframe containing property and selected descriptors values for the external validation set
n
Numbers of selected descriptors of the regression (determined using select_MLR)
Value
Rext,Rext2
return a list containing the value of the determination coefficient of the test set and of the external validation set
Graphe_3sets.tiff
Image representing experimental values vs predicted values for the all three sets
Examples
# This function have to be run last!
## "Test_set.csv" should be with the following form
## ID property SelectedDesc1 SelectedDesc2 ...
# new_nom<-'Test_set.csv'
# newdata<-read.csv(new_nom,header=TRUE , sep=" ")
# mynewdata=newdata[,2:dim[2]]
## "External_set.csv" should be with the following form
## ID property SelectedDesc1 SelectedDesc2 ...
# new_nom2<-'External_set.csv'
# newdata2<-read.csv(new_nom2,header=TRUE , sep=" ")
# mynewdata2=newdata2[,2:dim[2]]
#graphe_3Sets(fit,mynewdata,mynewdata2,dim(MLR)[2])