Computes a Bayesian Ridge Regression on a synthetic dataset. See

class sklearn.dummy.DummyRegressor(strategy='mean', constant=None, quantile=None)

Every estimator has its advantages and drawbacks. Its generalization error can be decomposed in terms of bias, variance and noise. The

Sample usage of Nearest Centroid classification. It will plot the decision boundaries for each class.