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Developing scikit-learn estimators — scik...
SGDClassifier ([[ 1 , 2 ], [ 2 , 3 ]], [ - 1 , 1 ]) # WRONG! Ideally,...modified if param1 > 1 : param2 += 1 self . param1 = param1...scikit-learn.org/stable/developers/develop.html -
Illustration of Gaussian process classification...
kernels = [ 1.0 * RBF ( length_scale = 1.15 ), 1.0 * DotProduct...)[:, 1 ] Z = Z . reshape ( xx . shape ) plt . subplot ( 1 , 2...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpc_xor.html -
sklearn.cluster — scikit-learn 1.8.0 docu...
2003) [R2af9f5762274-1] . SpectralClustering Apply clustering...(Dhillon, 2001) [R0dd0f3306ba7-1] . affinity_propagation Perform...scikit-learn.org/stable/api/sklearn.cluster.html -
Plot randomly generated multilabel dataset R...
1 ], color = COLORS . take (( Y * [ 1 , 2 , 4 ]) ....n_labels = 1 ) ax1 . set_title ( "n_labels=1, length=50"...scikit-learn.org/stable/auto_examples/datasets/plot_random_multilabel_dataset.html -
A demo of the mean-shift clustering algorithm &...
centers = [[ 1 , 1 ], [ - 1 , - 1 ], [ 1 , - 1 ]] X , _ = make_blobs...matplotlib.pyplot as plt plt . figure ( 1 ) plt . clf () colors = [ "#dede00"...scikit-learn.org/stable/auto_examples/cluster/plot_mean_shift.html -
adjusted_rand_score — scikit-learn 1.8.0 ...
1 , 1 ], [ 0 , 0 , 1 , 1 ]) 1.0 >>> adjusted_rand_score...adjusted_rand_score ([ 0 , 0 , 1 , 1 ], [ 1 , 1 , 0 , 0 ]) 1.0 Labelings that...scikit-learn.org/stable/modules/generated/sklearn.metrics.adjusted_rand_score.html -
ColumnTransformer — scikit-learn 1.8.0 do...
1. , 2. , 2. ], ... [ 1. , 1. , 0. , 1. ]]) >>>...scikit-learn 1.1 Release Highlights for scikit-learn 1.1 Release Highlights...scikit-learn.org/stable/modules/generated/sklearn.compose.ColumnTransformer.html -
class_likelihood_ratios — scikit-learn 1....
1 , 0 , 1 , 0 ], [ 1 , 1 , 0 , 0 , 0 ]) (1.5, 0.75)...LR+ ranges from 1.0 to infinity. A LR+ of 1.0 indicates that...scikit-learn.org/stable/modules/generated/sklearn.metrics.class_likelihood_ratios.html -
VotingClassifier — scikit-learn 1.8.0 doc...
([[ - 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.ensemble.VotingClassifier.html -
OrdinalEncoder — scikit-learn 1.8.0 docum...
inverse_transform ([[ 1 , 0 ], [ 0 , 1 ]]) array([['Male', 1], ['Female',... =- 1 ) . fit_transform ( X ) array([[ 1., 0.], [ 0., 1.], [...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OrdinalEncoder.html