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ClassNamePrefixFeaturesOutMixin — scikit-learn ...
shape [ 1 ] ... return self >>> X = np . array ([[ 1 , 2 ], [...scikit-learn.org/stable/modules/generated/sklearn.base.ClassNamePrefixFeaturesOutMixin.html -
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 -
fetch_file — scikit-learn 1.8.0 documentation
delay = 1 ) [source] # Fetch a file from...re-downloading. Added in version 1.6. Parameters : url str URL of...scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_file.html -
get_config — scikit-learn 1.8.0 documentation
Skip to main content Back to top Ctrl + K GitHub Choose version get_config # sklearn. get_config ( ) [source] # Retri...scikit-learn.org/stable/modules/generated/sklearn.get_config.html -
PLSRegression — scikit-learn 1.8.0 documentation
PLSRegression >>> X = [[ 0. , 0. , 1. ], [ 1. , 0. , 0. ], [ 2. , 2. ,...4. ]] >>> y = [[ 0.1 , - 0.2 ], [ 0.9 , 1.1 ], [ 6.2 , 5.9 ],...scikit-learn.org/stable/modules/generated/sklearn.cross_decomposition.PLSRegression.html -
PLSSVD — scikit-learn 1.8.0 documentation
array ([[ 0. , 0. , 1. ], ... [ 1. , 0. , 0. ], ... [ 2. ,...np . array ([[ 0.1 , - 0.2 ], ... [ 0.9 , 1.1 ], ... [ 6.2 ,...scikit-learn.org/stable/modules/generated/sklearn.cross_decomposition.PLSSVD.html -
load_wine — scikit-learn 1.8.0 documentation
target [[ 10 , 80 , 140 ]] array([0, 1, 2]) >>> list (...(classification). Added in version 0.18. The wine dataset is a classic...scikit-learn.org/stable/modules/generated/sklearn.datasets.load_wine.html -
fetch_species_distributions — scikit-learn 1.8....
Added in version 1.5. delay float, default=1.0 Number of seconds...True , n_retries = 3 , delay = 1.0 ) [source] # Loader for species...scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_species_distributions.html -
ExtraTreesClassifier — scikit-learn 1.8.0 docum...
be [{0: 1, 1: 1}, {0: 1, 1: 5}, {0: 1, 1: 1}, {0: 1, 1: 1}] instead...ate=0) >>> clf . predict ([[ 0 , 0 , 0 , 0 ]]) array([1]) apply...scikit-learn.org/stable/modules/generated/sklearn.ensemble.ExtraTreesClassifier.html -
MiniBatchNMF — scikit-learn 1.8.0 documentation
([[ 1 , 1 ], [ 2 , 1 ], [ 3 , 1.2 ], [ 4 , 1 ], [ 5 , 0.8 ],...scikit-learn 1.1 Release Highlights for scikit-learn 1.1 On this page...scikit-learn.org/stable/modules/generated/sklearn.decomposition.MiniBatchNMF.html