Warning DEPRECATED class

class sklearn.kernel_approximation.AdditiveChi2Sampler(sample_steps=2, sample_interval=None)

Due to the few points in each dimension and the straight line that linear regression uses to follow these points as well as it can, noise

sklearn.metrics.pairwise.manhattan_distances(X, Y=None, sum_over_features=True, size_threshold=500000000.0)

class sklearn.feature_extraction.text.TfidfVectorizer(input=u'content', encoding=u'utf-8', decode_error=u'strict',

sklearn.datasets.load_files(container_path, description=None, categories=None, load_content=True, shuffle=True, encoding=None, decode_error='strict'

class sklearn.model_selection.RandomizedSearchCV(estimator, param_distributions, n_iter=10, scoring=None, fit_params=None

Semi-supervised learning is a situation in which

class sklearn.calibration.CalibratedClassifierCV(base_estimator=None, method='sigmoid', cv=3)

class sklearn.random_projection.GaussianRandomProjection(n_components='auto', eps=0.1, random_state=None)