experiments.baselines.random_forest.RandomForestClassifierBaseline¶
- class RandomForestClassifierBaseline(**rf_kwargs)¶
Bases:
SupervisedExperimentBaseline
- __init__(**rf_kwargs)¶
Implements a random forest classifier baseline for a binary classification task
- __repr__()¶
Return repr(self).
Methods
- predict(theta, X)¶
Use the trained model to predict positive class probabilities theta isn’t used here because there are no fitted parameters in random forests. :param theta: Model weights, None in this case :param X: features :type X: 2D np.ndarray
- train(X, Y)¶
Instantiate a new model instance and train (fit) it to the training data, X,y :param X: features :type X: 2D np.ndarray :param y: labels :type y: 1D np.ndarray