A 1D regression with decision tree. The

class sklearn.naive_bayes.GaussianNB(priors=None)

sklearn.feature_selection.chi2(X, y)

This example employs several unsupervised learning techniques to extract the stock market structure from variations in historical quotes. The quantity

The sklearn

For greyscale image data where pixel values can be interpreted as degrees of blackness on a white background, like handwritten

This example is based on Section 5.4.3 of ?Gaussian Processes for Machine Learning? [RW2006]. It illustrates an example of complex kernel

class sklearn.cluster.DBSCAN(eps=0.5, min_samples=5, metric='euclidean', algorithm='auto', leaf_size=30, p=None, n_jobs=1)

class sklearn.gaussian_process.kernels.RBF(length_scale=1.0, length_scale_bounds=(1e-05, 100000.0))

sklearn.metrics.roc_auc_score(y_true, y_score, average='macro', sample_weight=None)