function?[tree_model]?=?buildDecisionTree（train_datatrain_labelfeat_typefeature_indexprediction_type）
%prediction_type?means?the?object?type?classification?or?regression
%0?means?classification?and?1?means?regression
num_of_feat?=?length（feat_type）;
num_of_data?=?size（train_data1）;

if?（num_of_feat?==?1）?||?（length（unique（train_label））?==?1）?||?num_of_data?????%type域表示節點類型，0表示葉節點，1表示非葉結點
????tree_model.type?=?0;
????if?prediction_type?==?0
????????%設置葉節點的預測值
????????tree_model.pre?=?FindMostFeat（train_label）;
????else
????????tree_model.pre?=?mean（train_label）;
????end
????%set?the?other?fileds?not?be?used
????tree_model.split_feat?=?-1;
????tree_model.split_value?=?-1;
????tree_model.child?=?[];
else
????[split_feat?split_value]?=?FindSplitFeat（train_data?train_label?feat_type0）;
????tree_model.split_feat?=?feature_index（split_feat）;
????tree_model.type?=?1;
????tree_model.pre?=?FindMostFeat（train_label）;
????if?feat_type（split_feat）?==?0
????????%numeric?feature
????????tree_model.split_value?=?split_value;
????????train_set1?=?train_data（train_data（:split_feat）?????????train_set2?=?train_data（train_data（:split_feat）?>=?split_value:）;
????????train_set1（:split_feat）?=?[];
????????train_set2（:split_feat）?=?[];
????????if?isempty（train_set1）?||?isempty（train_set2）
????????????tree_model.type?=?0;
????????????if?prediction_type?==?0
????????????%設置葉節點的預測值
????????????????tree_model.pre?=?FindMostFeat（train_label）;
????????????else
????????????????tree_model.pre?=?mean（train_label）;
????????????end
????????????%set?the?other?fileds?not?be?used
????????????tree_model.split_feat?=?-1;
????????????tree_model.split_value?=?-1;
????????????tree_model.child?=?[];
????????????return
????????end
????????train_label1?=?train_label（train_data（:split_feat）?????????train_label2?=?train_label（train_data（:split_feat）?>=?split_value:）;
????????feat_type（split_feat）?=?[];
????????feature_index（split_feat）?=?[];
????????tree_model.child?=?[buildDecisionTree（train_set1train_label1feat_typefeature_indexprediction_type）buildDecisionTree（train_set2train_label2feat_typefeature_indexprediction_type）];
????else
????????%nominal?feature
????????current_feat_value?=?split_value;
????????num_of_feat_value?=?length（current_feat_value）;
????????tree_model.split_value?=?split_value;
????????tree_model.child?=?[];
????????feat_type（split_feat）?=?[];
????????feature_index（split_feat）?=?[];
????????tree_child_empty?=?0;
????????for?i?=?1:num_of_feat_value
????????????sub_train_set?=?train_data（train_data（:split_feat）?==?current_feat_value（i）:）;
????????????sub_train_set（:split_feat）?=?[];
????????????if?isempty（sub_train_set）
????????????????tree_child_empty?=?1;
????????????end
????????end
????????if?tree_child_empty
????????????tree_model.type?=?0;
????????????if?prediction_type?==?0
????????????%設置葉節點的預測值
????????????????tree_model.pre?=?Fi

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????文件????????1405??2013-10-16?16:58??DecisionTreePrediction.m
?????文件????????3802??2013-10-16?16:57??buildDecisionTree.m
?????文件?????????371??2013-10-05?13:29??CalcEntropy.m
?????文件?????????259??2013-10-06?21:46??CalcLeaves.m
?????文件????????1004??2013-10-16?14:18??DecisionTree.m
?????文件?????????391??2013-10-06?11:33??FindMostFeat.m
?????文件????????4866??2013-10-06?20:57??FindSplitFeat.m
?????文件?????????532??2013-10-05?14:31??choose_split_for_numeric.m
?????文件????????1038??2013-10-16?14:30??main.m