Description: Learning_random.m: randomly selected sample, randomly selected sample from (90) pool the The deleted version space tree quantity activeLearning.m: selecting a sample from the pool based on the principle of maximum entropy, delete the number of version space tree getlabel.m: According to the tree and the test sample obtained according to the class standard getTrees.m the tree: from the tree structure (randomly generated), randomly selected a certain number of trees (the leaves of the tree node class marked randomly adding ) RandomCreateTree_d_unbalance: According to the sample point cut point unbalanced cut point construction tree, RandomCreateTree_d_all.m: construction of the tree randomdata.m all sample points cut point: given the value of the property, manufacturing data randomselect.m: random data Select as part showTree.m: tree structure test.m: tree, the test sample is given to get the correct rate
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代码\test.m
....\getTrees.m
....\RandomCreateTree_d_all.m
....\showTree.m
....\getlabel.m
....\randomdata.m
....\Learning_random.m
....\randomselect.m
....\activeLearning.m
....\RandomCreateTree_d_unbalance.m
....\readme.txt
数据\iris.data
....\treedata_iris.txt
....\traindata_iris.txt
....\testdata_iris.txt
....\result_iris_random2tree.txt
....\matlab_iris.mat
....\result_iris_random7sample.txt
....\readme.txt
....\复件 result_iris_random2tree.txt
....\总结.txt
....\复件 result_iris_random7sample.txt
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