|Function:||Multi-dimensional decision tree algorithm|
|Input Type:||xlsx, discrete|
|Input from Agent:||Dizzy, as integer representation|
|Output Type:||Set of decision rules, confusion matrix|
|Output to Agent:||Advice, Ceres, Juno|
Creates a multi-dimensional decision tree based on information gain (and their significance). It creates a number of root nodes and child nodes at once (the number is based on the maximum allowed and the minimum significance and information gain values). The branches of the tree are examined further on predictive value, where the best ones are used as a final prediction model - or as input to a following agent.