Matlab decision tree

Question

I am trying to make a decision tree but the outcome is strange and I can't figure out where is wrong. There are seven variables, each of which I use 1 or 2 to represent their meaning, for example, for variable 1 the number 1 is warm and 2 is cold, for variable 2 the number 1 is yes and 2 is no.

vars = {'TEMP' 'SKIN' 'BIRTH' 'AQUATIC' 'AERIAL' 'LEGS' 'HIBER'};
x = [1 1 1 2 2 1 2
     2 2 2 2 2 2 1
     2 2 2 1 2 2 2
     1 1 1 1 2 2 2
     2 1 2 1 2 1 1
     2 2 2 2 2 1 2
     1 1 1 2 1 1 1
     1 1 2 2 1 1 2
     1 1 1 2 2 1 2
     2 2 1 1 2 2 2
     2 2 2 1 2 1 2
     1 1 2 1 2 1 2
     1 1 1 2 2 1 1
     2 2 2 1 2 2 2
     2 1 2 1 2 1 1];
s = {'M';'R';'F';'M';'A';'R';'M';'B';'M';'F';'R';'B';'M';'F';'A'};
y = cellstr(s);
t = classregtree(x, y, 'method','classification', 'names',vars,...
                 'categorical',[1 7], 'prune','off');
view(t) 

The outcome is only one step tree without other information. What is wrong with this?

Answer 1

I'm not an expert of decision trees, anyway, playing a little bit with the parameters of classregtree ( minparent , to be exact):

vars = {'TEMP' 'SKIN' 'BIRTH' 'AQUATIC' 'AERIAL' 'LEGS' 'HIBER'};

x = [1 1 1 2 2 1 2
     2 2 2 2 2 2 1
     2 2 2 1 2 2 2
     1 1 1 1 2 2 2
     2 1 2 1 2 1 1
     2 2 2 2 2 1 2
     1 1 1 2 1 1 1
     1 1 2 2 1 1 2
     1 1 1 2 2 1 2
     2 2 1 1 2 2 2
     2 2 2 1 2 1 2
     1 1 2 1 2 1 2
     1 1 1 2 2 1 1
     2 2 2 1 2 2 2
     2 1 2 1 2 1 1];

y = {'M';'R';'F';'M';'A';'R';'M';'B';'M';'F';'R';'B';'M';'F';'A'};

t = classregtree(x,y,'method','classification','Names',vars, ...
    'categorical',[1 7],'prune','off','minparent',1);

view(t);

I've been able to reproduce something that looks fine. Anyway, since Matlab release 2011A, classregtree has become obsolete and has been superseded by fitrtree (RegressionTree) and fitctree (ClassificationTree) functions ( classregtree is being kept for retrocompatibility reasons only). I recommend you to update your code and use those functions instead:

t = fitctree(x,y,'PredictorNames',vars, ...
    'CategoricalPredictors',{'TEMP' 'HIBER'},'Prune','off','MinParentSize',1);