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Results 31 - 40 of 576 for c (0.07 sec)
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plot_classifier_comparison.py
C=0.025, random_state=42), SVC(gamma=2, C=1, random_state=42),...ax.scatter(X_train[:, 0], X_train[:, 1], c=y_train, cmap=cm_bright, edgecolors="k")...scikit-learn.org/stable/_downloads/2da0534ab0e0c8241033bcc2d912e419/plot_classifier_comparison.py -
3.2. Tuning the hyper-parameters of an estimato...
Typical examples include C , kernel and gamma for Support...param_grid : param_grid = [ { 'C' : [ 1 , 10 , 100 , 1000 ], 'kernel'...scikit-learn.org/stable/modules/grid_search.html -
sklearn.datasets.make_multilabel_classification...
choose a class c: c ~ Multinomial(theta) pick the...a word: w ~ Multinomial(theta_c) In the above process, rejection...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_multilabel_classification.html -
grid_search.rst.txt
= [ {'C': [1, 10, 100, 1000], 'kernel': ['linear']}, {'C': [1,...classes. Typical examples include ``C``, ``kernel`` and ``gamma`` for...scikit-learn.org/stable/_sources/modules/grid_search.rst.txt -
clustering.rst.txt
\sum_{q=1}^k n_q (c_q - c_E) (c_q - c_E)^T with :math:`C_q` the set...math:: C = \left[\begin{matrix} C_{00} & C_{01} \\ C_{10} & C_{11}...scikit-learn.org/stable/_sources/modules/clustering.rst.txt -
10 PRINT "HELLO METAFILTER"; 20 GOTO 10 | MetaF...
-> Java -> C++ & HLSL & C# (third job) -> C++ & C#, and sometimes...that did nothing in C. Includes? main? return? C'mon, just give me...www.metafilter.com/203575/10-PRINT-HELLO-METAFILTER-20-GOTO-10 -
sklearn.metrics.confusion_matrix — scikit-learn...
a confusion matrix \(C\) is such that \(C_{i, j}\) is equal to...negatives is \(C_{0,0}\) , false negatives is \(C_{1,0}\) , true...scikit-learn.org/stable/modules/generated/sklearn.metrics.confusion_matrix.html -
sklearn.linear_model.LogisticRegressionCV — sci...
the best C is the average of the C’s that correspond...folds, and the coefs and the C that corresponds to the best score...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegressionCV.html -
Universal Profiling - continuous profiling that...
www.elastic.co/observability/universal-profiling -
sklearn.svm.SVR — scikit-learn 1.4.2 documentation
C = 1.0 , epsilon = 0.1 , shrinking...free parameters in the model are C and epsilon. The implementation...scikit-learn.org/stable/modules/generated/sklearn.svm.SVR.html