sklearn.datasets.get_data_home(data_home=None)

Warning DEPRECATED

class sklearn.model_selection.ParameterGrid(param_grid)

Demonstrate how model complexity influences both prediction accuracy and computational performance. The dataset is the Boston Housing dataset (resp. 20 Newsgroups)

For some applications the amount of examples, features (or both) and/or the speed at which they need to be processed are challenging for traditional

class sklearn.exceptions.DataDimensionalityWarning

When performing classification you often want not only to predict the class label, but also obtain a probability of the respective label. This probability gives you

class sklearn.pipeline.Pipeline(steps)

An example to compare multi-output regression with random forest and the

sklearn.metrics.pairwise.euclidean_distances(X, Y=None, Y_norm_squared=None, squared=False, X_norm_squared=None)