added figure

doc/src/DecisionTrees/DecisionTrees.do.txt

@@ -35,8 +35,9 @@ given some assumptions, make predictions about the target feature value
 !split
 ===== A typical Decision Tree with its pertinent Jargon, Classification Problem =====
 
-Figure to come here.
+FIGURE: [DataFiles/cancer.png, width=600 frac=0.8]
 
+This tree was produced using the Wisconsin cancer data (discussed here as well, see code examples below) using _Scikit-Learn_'s decision tree classifier. Here we have used the so-called _gini_ index (see below) to split the various branches.
 
 
 
@@ -1700,3 +1701,6 @@ print("Minimum validation MSE:", min_val_error)
 !split
 ===== XGBoost: Extreme Gradient Boosting =====
 
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