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hinge_loss — scikit-learn 1.6.1 documentation
scikit-learn.org/stable/modules/generated/sklearn.metrics.hinge_loss.html -
GaussianProcessClassifier — scikit-learn 1.6.1 ...
Returns : C ndarray of shape (n_samples,)...for classification. Returns : C array-like of shape (n_samples,...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.GaussianProcessClassifier.html -
1.6. Nearest Neighbors — scikit-learn 1.6.1 doc...
point \(C\) , then we know that points \(A\) and \(C\) are very...\[p_{i}=\sum\limits_{j \in C_i}{p_{i j}}\] where \(C_i\) is the set of...scikit-learn.org/stable/modules/neighbors.html -
NBC News special features and projects | NBC News
C. Boston Bay Area South Florida...fine print changed. Blast the A/C? Throw out half your lunch? Share...www.nbcnews.com/specials -
linear_model.rst.txt
``C`` is given by ``alpha = 1 / C`` or ``alpha =...:func:`sklearn.svm.l1_min_c` allows to calculate the lower bound for C in order...scikit-learn.org/stable/_sources/modules/linear_model.rst.txt -
MiniBatchKMeans — scikit-learn 1.6.1 documentation
the data will be converted to C ordering, which will cause a memory...copy if the given data is not C-contiguous. If a sparse matrix...scikit-learn.org/stable/modules/generated/sklearn.cluster.MiniBatchKMeans.html -
3.5. Validation curves: plotting scores to eval...
param_name = "C" , param_range = np . logspace..."linear" ), X , y , param_name = "C" , param_range = np . logspace...scikit-learn.org/stable/modules/learning_curve.html -
set_config — scikit-learn 1.6.1 documentation
scikit-learn.org/stable/modules/generated/sklearn.set_config.html -
neighbors.rst.txt
:math:`C`, then we know that points :math:`A` and :math:`C` are...p_{i}=\sum\limits_{j \in C_i}{p_{i j}} where :math:`C_i` is the set of...scikit-learn.org/stable/_sources/modules/neighbors.rst.txt -
PassiveAggressiveClassifier — scikit-learn 1.6....
C = 1.0 , fit_intercept = True ,...the User Guide . Parameters : C float, default=1.0 Maximum step...scikit-learn.org/stable/modules/generated/sklearn.linear_model.PassiveAggressiveClassifier.html