| Library: | xclust |
| See also: | cartsplitclass |
| Quantlet: | cartsplitregr | |
| Description: | builds the regression tree. |
| Usage: | Tree = cartsplitregr(VarMatrix,ClassVector,MinSize) | |
| Input: | ||
| VarMatrix | n x m matrix, variables | |
| ClassVector | n x 1 vector, classes | |
| MinSize | scalar, stop condition, minimum number of observations in terminal node | |
| Output: | ||
| Tree | list of vectors, composed of: Variable - number of variable of the split questions SplitValue - critical value of the question Class - dominating class of the current node (class with maximum number of observations) Impurity - missclassification error for each node (between 0 and 1) NumberOfPoints - total number of points (all classes) in current node ParentNode - records of parent node Index - used for transformation from XploRe to dll and back DrawIndex - used for drawing trees in XploRe | |
library("xclust");
x1 = #(0.898473738, 0.852630806, 0.539114276, 0.241251175, 0.476125641, 0.284315731, 0.0181318590)
x2 = #(0.255756912, 0.303028656, 0.146633917, 0.121365982, 0.4111506, 0.97609203, 0.514180304)
x = x1~x2;
y = #(1.1, 1.2, 1.3, 0.1, 1.45, 2.2, 1.465)
tr = cartsplitregr(x,y,1)
cartdisptree(tr)
Generates data structure tr representing a binary tree.