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validation_curve — scikit-learn 1.5.2 documenta...
str can be an expression like ‘2*n_jobs’. verbose int, default=0...scikit-learn.org/stable/modules/generated/sklearn.model_selection.validation_curve.html -
XML results output
2 11.1 11.0 10.3 10.2 10.1 10.0 9.4 9.3 9.2 9.1 9.0 8.0...13.4 13.3 13.2 13.1 13.0 12.7 12.6 12.5 12.4 12.3 12.2 12.1 12.0...fess.codelibs.org/4.0/user/xml-response.html -
TfidfVectorizer — scikit-learn 1.5.2 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 -
haversine_distances — scikit-learn 1.5.2 docume...
data must be 2. \[D(x, y) = 2\arcsin[\sqrt{\sin^2((x_{lat} - y_{lat})...y_{lat}) / 2) + \cos(x_{lat})\cos(y_{lat})\ sin^2((x_{lon} -...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.haversine_distances.html -
Gradient Boosting regularization — scikit-learn...
2" , "turquoise" , { "learning_rate" : 0.2 , "subsample"..."learning_rate=0.2, subsample=0.5" , "gray" , { "learning_rate" : 0.2 , "subsample"...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_regularization.html -
MaxAbsScaler — scikit-learn 1.5.2 documentation
2. ], ... [ 2. , 0. , 0. ], ... [ 0. ,...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.MaxAbsScaler.html -
unique_labels — scikit-learn 1.5.2 documentation
2 , 3 , 4 ], [ 2 , 2 , 3 , 4 ]) array([1, 2, 3, 4]) >>>...unique_labels ([ 1 , 2 , 10 ], [ 5 , 11 ]) array([ 1, 2, 5, 10, 11])...scikit-learn.org/stable/modules/generated/sklearn.utils.multiclass.unique_labels.html -
Probability Calibration curves — scikit-learn 1...
add_subplot ( gs [: 2 , : 2 ]) calibration_displays = {}...histogram grid_positions = [( 2 , 0 ), ( 2 , 1 ), ( 3 , 0 ), ( 3 ,...scikit-learn.org/stable/auto_examples/calibration/plot_calibration_curve.html -
SVM Exercise — scikit-learn 1.5.2 documentation
: 2 ] y = y [ y != 0 ] n_sample =...scikit-learn.org/stable/auto_examples/exercises/plot_iris_exercise.html -
manhattan_distances — scikit-learn 1.5.2 docume...
2 ], [ 3 , 4 ]], [[ 1 , 2 ], [ 0 , 3 ]]) array([[0., 2.],...]], [[ 2 ]]) array([[1.]]) >>> manhattan_distances ([[ 2 ]], [[...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.manhattan_distances.html