- Sort Score
- Num 10 results
- Language All
- Labels All
Results 341 - 350 of over 10,000 for 1 (1.41 seconds)
Filter
-
Plot classification probability — scikit-learn ...
GaussianProcessClass ( kernel = 1.0 * RBF ([ 1.0 , 1.0 ])), "Logistic regression...LogisticRegression ( C = 0.1 ), "Logistic regression \n (C=1)" : LogisticRegression...scikit-learn.org/stable/auto_examples/classification/plot_classification_probability.html -
TheilSenRegressor — scikit-learn 1.8.0 document...
means 1 unless in a joblib.parallel_backend context. -1 means...the number of features (plus 1 if fit_intercept=True) and the...scikit-learn.org/stable/modules/generated/sklearn.linear_model.TheilSenRegressor.html -
make_circles — scikit-learn 1.8.0 documentation
int64(1), np.int64(1), np.int64(1), np.int64(0), np.int64(0)]...outer circle in the range [0, 1) . Returns : X ndarray of shape...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_circles.html -
LassoLarsIC — scikit-learn 1.8.0 documentation
[ - 1 , 1 ], [ 0 , 0 ], [ 1 , 1 ], [ 2 , 2 ]] >>>...fit_intercept . Added in version 1.1. Attributes : coef_ array-like...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LassoLarsIC.html -
permutation_test_score — scikit-learn 1.8.0 doc...
p-value is 1/(n_permutations + 1), the worst is 1.0. Notes This...means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn.org/stable/modules/generated/sklearn.model_selection.permutation_test_score.html -
RidgeClassifier — scikit-learn 1.8.0 documentation
converts the target values into {-1, 1} and then treats the problem...sklearn.linear_model. RidgeClassifier ( alpha = 1.0 , * , fit_intercept = True ,...scikit-learn.org/stable/modules/generated/sklearn.linear_model.RidgeClassifier.html -
make_swiss_roll — scikit-learn 1.8.0 documentation
is from Marsland [1] . References [ 1 ] ( 1 , 2 ) S. Marsland,...from Stephen Marsland’s code [1] . Parameters : n_samples int,...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_swiss_roll.html -
zero_one_loss — scikit-learn 1.8.0 documentation
1 ], [ 1 , 1 ]]), np . ones (( 2 , 2...zero_one_loss >>> y_pred = [ 1 , 2 , 3 , 4 ] >>> y_true = [ 2...scikit-learn.org/stable/modules/generated/sklearn.metrics.zero_one_loss.html -
Lars — scikit-learn 1.8.0 documentation
n_nonzero_coefs = 1 ) >>> reg . fit ([[ - 1 , 1 ], [ 0 , 0 ], [ 1 , 1 ]], [...[ - 1.1111 , 0 , - 1.1111 ]) Lars(n_nonzero_coefs=1) >>> print...scikit-learn.org/stable/modules/generated/sklearn.linear_model.Lars.html -
IsotonicRegression — scikit-learn 1.8.0 documen...
1 , .2 ]) array([1.8628, 3.7256]) fit (...n_samples = 10 , n_features = 1 , random_state = 41 ) >>> iso_reg...scikit-learn.org/stable/modules/generated/sklearn.isotonic.IsotonicRegression.html