Why it is 94? corss-validation for regression tree problem.

1 次查看（过去 30 天）
Salad Box
Salad Box 2019-1-17
Hi,
Example shown on the page below.
https://uk.mathworks.com/help/stats/regressiontree.crossval.html
load carsmall
X = [Acceleration Displacement Horsepower Weight]; % X is 100 by 4.
Mdl = fitrtree(X,MPG); % grow a regression tree using the entire data set.
CVMdl = crossval(Mdl); % cross-validate the regression tree using 10-fold cross-validation
As I looked into CVMdl (the RegressionPartitionedModel cross-validated model), it shows the observation number used in each fold is 94. Why is it 94 not 90? See screenshot below.
Untitled.png
Since X is 100 by 4, showing there are 100 observations to start. To have 10 folds, it means they should divide X into 90 training data and 10 test data. So I couldn't figure out why it is 94 training data instead of 90.
Please help.

请先登录，再回答此问题。

回答（0 个）

类别

在 Help Center 和 File Exchange 中查找有关 Gaussian Process Regression 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by