Assess Learners

I implement and evaluate three learning algorithms as Python classes: A "classic" Decision Tree learner, a Random Tree learner, and a Bootstrap Aggregating learner. The goal for my learner is to return a continuous numerical result (not a discrete result). I write my own code for Decision Tree learning, Random Tree learning and bagging. My learners should be able to handle any number of dimensions in X from 2 to N. All of the decision tree learners I create are implemented using a matrix data representation (numpy ndarray).

Built With

• python