Crossval and regressiontree.fit - how does crossval works?

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Tania
Tania 2014-6-30
评论： Tania 2014-7-9
Hey!:) I am using Regressiontree.fit in order to do build a decision tree for my data. If I want it to do cross validation automatic I have to include (‘crossval’,’on’), right? I have done it, but I am not quite sure what matlab has done exactly? What does KFold 10 means? How does this automatic crossvalidation works?
Thanks a lot for your help!
Please find my code below: >> rtree=RegressionTree.fit(X,price,'crossval', 'on' )
rtree =
classreg.learning.partition.RegressionPartitionedModel
CrossValidatedModel: 'Tree'
PredictorNames: {'x1' 'x2' 'x3'}
CategoricalPredictors: []
ResponseName: 'Y'
NObservations: 5255
KFold: 10
Partition: [1x1 cvpartition]
ResponseTransform: 'none'

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Shashank Prasanna
Shashank Prasanna 2014-6-30
编辑：Shashank Prasanna 2014-6-30
What does KFold 10 means?
https://en.wikipedia.org/wiki/Cross-validation_(statistics)
matlab has done exactly?
MATLAB has performed kfold cross-validation and returned a partitioned model instead of a single regression tree. Crossvalidation allows you to assess the predictive performance of model on cross-validated data. You can access these methods using the output of a cross validated model: kfoldfun, kfoldLoss, kfoldPredict.
Alternatively you can fit a model and then call cross val this way:
rtree = RegressionTree.fit(X,price);
rcrossvaltree = crossval(rtree);
Read more here (also includes examples):
http://www.mathworks.com/help/stats/regressionpartitionedmodel-class.html
http://www.mathworks.com/help/stats/regressiontree.crossval.html
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