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SGDOneClassSVM — scikit-learn 1.8.0 docum...
array ([[ - 1 , - 1 ], [ - 2 , - 1 ], [ 1 , 1 ], [ 2 , 1 ]]) >>>...deprecated in version 1.8 and will raise an error in 1.10. Use values...scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDOneClassSVM.html -
Hyperparameter — scikit-learn 1.8.0 docum...
n_elements = 1 , fixed = None ) [source] # A...the parameter. If n_elements>1, a pair of 1d array with n_elements...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Hyperparameter.html -
LinearDiscriminantAnalysis — scikit-learn...
([[ - 1 , - 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2...2 , 1 ], [ 3 , 2 ]]) >>> y = np . array ([ 1 , 1 , 1...scikit-learn.org/stable/modules/generated/sklearn.discriminant_analysis.LinearDiscriminantAnalysi... -
clone — scikit-learn 1.8.0 documentation
>>> X = [[ - 1 , 0 ], [ 0 , 1 ], [ 0 , - 1 ], [ 1 , 0 ]] >>>...>>> y = [ 0 , 0 , 1 , 1 ] >>> classifier = LogisticRegression...scikit-learn.org/stable/modules/generated/sklearn.base.clone.html -
trustworthiness — scikit-learn 1.8.0 docu...
1]. It is defined as \[T(k) = 1 - \frac{2}{nk (2n...(2n - 3k - 1)} \sum^n_{i=1} \sum_{j \in \mathcal{N}_{i}^{k}}...scikit-learn.org/stable/modules/generated/sklearn.manifold.trustworthiness.html -
spectral_clustering — scikit-learn 1.8.0 ...
array ([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7...random_state = 0 ... ) array([1, 1, 1, 0, 0, 0]) Gallery examples...scikit-learn.org/stable/modules/generated/sklearn.cluster.spectral_clustering.html -
make_multilabel_classification — scikit-l...
[array([1, 1, 0, 1, 0]), array([0, 1, 1, 1, 0]), array([0, 1, 0,...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_multilabel_classification.html -
SpectralClustering — scikit-learn 1.8.0 d...
array ([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7...clustering . labels_ array([1, 1, 1, 0, 0, 0]) >>> clustering...scikit-learn.org/stable/modules/generated/sklearn.cluster.SpectralClustering.html -
make_classification — scikit-learn 1.8.0 ...
class_sep = 1.0 , hypercube = True , shift = 0.0 , scale = 1.0 , shuffle...[np.int64(0), np.int64(0), np.int64(1), np.int64(1), np.int64(0)] Gallery...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_classification.html -
TSNE — scikit-learn 1.8.0 documentation
1 , 1 ], [ 1 , 0 , 1 ], [ 1 , 1 , 1 ]]) >>>...metric function. Added in version 1.1. init {“random”, “pca”} or ndarray...scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html