function?D?=?C4_5（train_features?train_targets?inc_node?region）

%?Classify?using?Quinlan‘s?C4.5?algorithm
%?Inputs:
%?features	??-?Train?features
%	targets	????-?Train?targets
%	inc_node????-?Percentage?of?incorrectly?assigned?samples?at?a?node
%???inc_node參數用于作為迭代結束的條件，我覺得就是葉子節點可以包含的最大的樣本數
%???inc_node參數太大的話會導致分類準確率下降，太小的話可能會導致過擬合
%	region	????-?Decision?region?vector:?[-x?x?-y?y?number_of_points]
%
%?Outputs
%	D			-?Decision?sufrace

%NOTE:?In?this?implementation?it?is?assumed?that?a?feature?vector?with?fewer?than?10?unique?values?（the?parameter?Nu）
%is?discrete?and?will?be?treated?as?such.?Other?vectors?will?be?treated?as?continuous

[Ni?M]		=?size（train_features）;%M是樣本數，Ni是樣本維數
inc_node????=?inc_node*M/100;
Nu??????????=?10;

%For?the?decision?region
N??????

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----

?????文件???????6771??2010-04-05?23:28??C4_5.m

-----------?---------??----------?-----??----

?????????????????6771????????????????????1