Decision tree implementation in MATlab
Kailin-an
matlab_help.ziph,w2.pdf
Evaluation Function • The object allows for functional evaluation, of the form ctree(X).
This is a shorthand way of calling the eval method of the classregtree class. The predicted species is the left leaf node at the bottom of the tree in the previous view.
• You can use a variety of methods of the classregtree class, such as cutvar and cuttype to get more information about the split at node 6 that makes the final distinction between versicolor and virginica:
>> var6 = cutvar(ctree,6)
>> type6 = cuttype(ctree,6)
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Implementation of Decision Trees
in Matlab.
h.w3.pdf
1- define two vectors a,b
2- find β0+β1
3- find mse
4- = β1+β2 *
5- t* = tinv(P,df)
6- =sqrt(mse)
7- = mean(a)
8- = sum((a – xbar).^2)
9- calculating confidence interval equation
10- calculating prediction interval equation
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Y 0x
eS X
xxS
Evaluation
