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Nearest Centroid Classification — scikit-learn ...
2 0.82 # Authors: The scikit-learn...dataset X = iris . data [:, : 2 ] y = iris . target # Create color...scikit-learn.org/stable/auto_examples/neighbors/plot_nearest_centroid.html -
TfidfVectorizer — scikit-learn 1.8.0 documentation
2) means unigrams and bigrams, and (2, 2) means only...default regexp selects tokens of 2 or more alphanumeric characters...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.TfidfVectorizer.html -
Regularization path of L1- Logistic Regression ...
= 2 ] y = y [ y != 2 ] Compute regularization...scikit-learn.org/stable/auto_examples/linear_model/plot_logistic_path.html -
Microsoft 365-Konnektor
2.0 oder höher Plugin-Installation.../usr/share/fess/app/WEB-INF/lib/ Methode 2: Aus Quellcode erstellen git clone...fess.codelibs.org/de/15.5/config/datastore/ds-microsoft365.html -
plot_pca_iris.zip
2 import mpl_toolkits.mplot3d #...X_reduced[:, 1], X_reduced[:, 2], c=iris.target, s=40, ) ax.set(...scikit-learn.org/stable/_downloads/99402c7ce7a6ab7fafcb48caa3c9447b/plot_pca_iris.zip -
Crafting a minimal reproducer for scikit-learn ...
n_features = 2 , n_redundant = 0 , n_informative = 2 , n_clusters_per_class...n_features ) y = rng . randint ( 0 , 2 , n_samples ) # binary target...scikit-learn.org/stable/developers/minimal_reproducer.html -
LatentDirichletAllocation — scikit-learn 1.8.0 ...
implementation is based on [1] and [2] . Added in version 0.17. Read...rule. References [ 1 ] ( 1 , 2 , 3 ) “Online Learning for Latent...scikit-learn.org/stable/modules/generated/sklearn.decomposition.LatentDirichletAllocation.html -
plot_kmeans_digits.rst.txt
PCA` to project into a 2-dimensional space and plot the...reduced_data = PCA(n_components=2).fit_transform(data) kmeans =...scikit-learn.org/stable/_sources/auto_examples/cluster/plot_kmeans_digits.rst.txt -
ClassNamePrefixFeaturesOutMixin — scikit-learn ...
2 ], [ 3 , 4 ]]) >>> MyEstimator...scikit-learn.org/stable/modules/generated/sklearn.base.ClassNamePrefixFeaturesOutMixin.html -
1.14. Semi-supervised learning — scikit-learn 1...
2. Label Propagation # Label propagation...be relaxed, to say \(\alpha=0.2\) , which means that we will always...scikit-learn.org/stable/modules/semi_supervised.html