Module stamm::tree
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[src]
Implements a very generic decision tree. This means that the data for an interior node and for leafs can be anything. The splitting criteria of the training set, the features used and the impurity computation can be implemented as required.
Structs
DecisionTree |
A decision tree for prediction all kinds of thing a decision tree can predict.
A leaf of this tree contains data of type |
TreeParameters |
Struct for learning a decision tree |
Enums
Binar |
There a two cases for a binary tree: Using the left child or the right one.
So here we have a |
Traits
TreeFunction |
A trait for describing the behavior of a learned tree.
A Tree which follows this behavior can accept data of type |
TreeLearnFunctions |
A trait for describing the behavior of a tree and the way it should be trained.
For training data of type |