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validation_curve — scikit-learn 1.7.2 documenta...
param_range = "C" , np . logspace ( - 8 , 3 , 10...scikit-learn.org/stable/modules/generated/sklearn.model_selection.validation_curve.html -
make_scorer — scikit-learn 1.7.2 documentation
param_grid = { 'C' : [ 1 , 10 ]}, ... scoring =...scikit-learn.org/stable/modules/generated/sklearn.metrics.make_scorer.html -
DecisionBoundaryDisplay — scikit-learn 1.7.2 do...
c = iris . target , edgecolor =...scatter ( X [:, 0 ], X [:, 1 ], c = iris . target , edgecolor =...scikit-learn.org/stable/modules/generated/sklearn.inspection.DecisionBoundaryDisplay.html -
7.3. Preprocessing data — scikit-learn 1.7.2 do...
“b” and “c” are their own categories, unknown..."a" ] * 5 + [ "b" ] * 20 + [ "c" ] * 10 + [ "d" ] * 3 + [ np ....scikit-learn.org/stable/modules/preprocessing.html -
hinge_loss — scikit-learn 1.7.2 documentation
Multiclass Hinge Loss Models by Robert C. Moore, John DeNero . Examples...scikit-learn.org/stable/modules/generated/sklearn.metrics.hinge_loss.html -
1.6. Nearest Neighbors — scikit-learn 1.7.2 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 -
plot_pca_iris.rst.txt
c=iris.target, s=40, ) ax.set( title="First...scikit-learn.org/stable/_sources/auto_examples/decomposition/plot_pca_iris.rst.txt -
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 1.7.2 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