experiments.baselines.random_classifiers.WeightedRandomClassifierBaseline

class WeightedRandomClassifierBaseline(weight)

Bases: RandomClassifierModel, SupervisedExperimentBaseline

__init__(weight)

Implements a classifier that always predicts that the positive class has prob=0.5, regardless of input

__repr__()

Return repr(self).

Methods

predict(theta, X)

Overrides parent method. Predict the probability of having the positive class label

Parameters:

• theta (numpy ndarray) – The parameter weights

• X (numpy ndarray) – The features

Returns:

predictions for each observation

Return type:

float

train(X, Y)

Train the model on the training data, X,y :param X: features :type X: 2D np.ndarray :param y: labels :type y: 1D np.ndarray