📄 prune_tree_points.m
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function T = prune_tree_points(T,A,B,min_points)
% PRUNE_TREE_POINTS prunes the decision tree T as follows: if any decision
% node misclassifies less than min_points points, then this decision
% node will be made a leaf node.
%
% T = prune_tree_points(T,A,B,min_points)
%
% T : matrix representing the decision tree generated by MSM-T algorithm
% A : matrix representing the point set A
% B : matrix representing the point set B
% min_points: the minimum allowable number of misclassified points at
% a decision node.
%
% ASSUME: the root node will never be pruned.
% n is the dimension of the points in set A,B
global n;
n = size(A,2);
% prune the tree
position = [ 1 ];
T = prune_points(T,A,B,min_points,0,[position, T(n+2,1)]); % prune left
T = prune_points(T,A,B,min_points,1,[position, T(n+3,1)]); % prune right
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