Algorithm 1: Decision tree algorithm pseudocode.

input: List of all explanatory variables ($\mathit{X}$), training dataset ($\mathit{D}$) output: Decision tree ($\mathit{D}\mathit{T}$) /1/ Start at the root node /2/ for each$X$ in $\mathit{X}$ do /3/ find the set S that minimizes the sum of the node impurities in the two child nodes in Equation (1) and choose the split $\left\{X^{*}\in S^{*}\right\}$ that produces the minimum overall $X$ and $S$ /4/ end /5/ if stopping criterion is reached then do /6/ stop /7/ else do /8/ apply step 2 to each child node in turn /9/ end /10/ return DT