Machine learning risk determination system for tree based models

A computer-implemented method for determining action codes in a tree-based decision model, the computer-implemented method comprising, as implemented by one or more computing devices within a risk determination system configured with specific executable instructions:

• assigning each feature in a tree-based decision model to an action code;
• initializing a risk sum for each action code;
• calculating, for all nodes in the tree-based decision model, a difference in risk between child nodes and respective parent nodes;
• updating the risk sum for each action code associated with the feature used in the decision for the node;
• determining the feature with the highest risk sum;
• and
• determining the action code associated with the determined feature.

Non-transitory computer readable medium storing computer executable instructions thereon, the computer executable instructions when executed cause a risk determination system to at least:

• assign each feature in a tree-based decision model to an action code;
• initialize a risk sum for each action code;
• calculate, for all nodes in the tree-based decision model, a difference in risk between child nodes and respective parent nodes;
• update the risk sum for each action code associated with the feature used in the decision for the node;
• determine the feature with the highest risk sum;
• and
• determine the action code associated with the determined feature.