Predict response of ensemble by resubstitution
Yfit = resubPredict(ens)
Yfit = resubPredict(ens,Name,Value)
A regression ensemble created with
comma-separated pairs of
the argument name and
Value is the corresponding value.
Name must appear inside single quotes (
' '). You can
specify several name and value pair arguments in any order as
Indices of weak learners in the ensemble ranging from
A vector of predicted responses to the training data, with
Find the resubstitution predictions of mileage from the
carsmall data, and look at their mean-squared difference from the training data.
carsmall data set and select horsepower and vehicle weight as predictors.
load carsmall X = [Horsepower Weight];
Train an ensemble of regression trees.
ens = fitrensemble(X,MPG,'Method','LSBoost','Learners','Tree');
Find the resubstitution predictions of
Yfit = resubPredict(ens);
Calculate the mean-squared difference of the resubstitution predictions from the training data.
MSE = mean((Yfit - ens.Y).^2)
MSE = 0.5836
Confirm that the result is the same as the result of
ans = 0.5836