Prediction Using Classification and Regression Trees
This example shows how to predict class labels or responses using trained classification and regression trees.
After creating a tree, you can easily predict responses for new data. Suppose Xnew
is new data that has the same number of columns as the original data X
. To predict the classification or regression based on the tree (Mdl
) and the new data, enter
Ynew = predict(Mdl,Xnew)
For each row of data in Xnew
, predict
runs through the decisions in Mdl
and gives the resulting prediction in the corresponding element of Ynew
. For more information on classification tree prediction, see the predict
. For regression, see predict
.
For example, find the predicted classification of a point at the mean of the ionosphere
data.
load ionosphere
CMdl = fitctree(X,Y);
Ynew = predict(CMdl,mean(X))
Ynew = 1x1 cell array
{'g'}
Find the predicted MPG
of a point at the mean of the carsmall
data.
load carsmall
X = [Horsepower Weight];
RMdl = fitrtree(X,MPG);
Ynew = predict(RMdl,mean(X))
Ynew = 28.7931
See Also
fitctree
| fitrtree
| ClassificationTree
| RegressionTree
| predict (CompactRegressionTree)
| predict (CompactClassificationTree)