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RandomForestClassifier — scikit-learn 1.7.0 doc...
[{0: 1, 1: 1}, {0: 1, 1: 5}, {0: 1, 1: 1}, {0: 1, 1: 1}] instead...instead of [{1:1}, {2:5}, {3:1}, {4:1}]. The “balanced” mode uses...scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html -
LinearDiscriminantAnalysis — scikit-learn 1.7.0...
([[ - 1 , - 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2...2 , 1 ], [ 3 , 2 ]]) >>> y = np . array ([ 1 , 1 , 1 , 2 , 2...scikit-learn.org/stable/modules/generated/sklearn.discriminant_analysis.LinearDiscriminantAnalysi... -
RandomizedSearchCV — scikit-learn 1.7.0 documen...
means 1 unless in a joblib.parallel_backend context. -1 means...… rank_test_score ‘rbf’ 0.1 0.80 … 1 ‘rbf’ 0.2 0.84 … 3 ‘rbf’...scikit-learn.org/stable/modules/generated/sklearn.model_selection.RandomizedSearchCV.html -
LatentDirichletAllocation — scikit-learn 1.7.0 ...
evaluate_every = -1 , total_samples = 1000000.0 , perp_tol = 0.1 , mean_change_tol...None, defaults to 1 / n_components . In [1] , this is called...scikit-learn.org/stable/modules/generated/sklearn.decomposition.LatentDirichletAllocation.html -
TfidfVectorizer — scikit-learn 1.7.0 documentation
ngram_range=(1 , 1) , max_df=1.0 , min_df=1 , max_features=None...ngram_range of (1, 1) means only unigrams, (1, 2) means unigrams...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.TfidfVectorizer.html -
GaussianNB — scikit-learn 1.7.0 documentation
([[ - 1 , - 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2...2 , 1 ], [ 3 , 2 ]]) >>> Y = np . array ([ 1 , 1 , 1 , 2 , 2...scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.GaussianNB.html -
SpectralClustering — scikit-learn 1.7.0 documen...
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 -
MaxAbsScaler — scikit-learn 1.7.0 documentation
-1. , 1. ], [ 1. , 0. , 0. ], [ 0. , 1. , -0.5]]) fit...= [[ 1. , - 1. , 2. ], ... [ 2. , 0. , 0. ], ... [ 0. , 1. , -...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.MaxAbsScaler.html -
NeighborhoodComponentsAnalysis — scikit-learn 1...
If 1, progress messages will be printed to stdout. If > 1, progress...<= min(n_features, n_classes - 1) we use 'lda' , as it uses labels...scikit-learn.org/stable/modules/generated/sklearn.neighbors.NeighborhoodComponentsAnalysis.html -
TSNE — scikit-learn 1.7.0 documentation
1 , 1 ], [ 1 , 0 , 1 ], [ 1 , 1 , 1 ]]) >>> X_embedded...metric function. Added in version 1.1. init {“random”, “pca”} or ndarray...scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html