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或者，从命令提示符: C : \ > cd C : \ opensearch - 3.3.2 C : \ opensearch...fess.bat 或者，从命令提示符: C : \ > cd C : \ fess - 15.4.0 C : \ fess - 15.4.0...fess.codelibs.org/zh-cn/15.4/install/run.html -
SVM Tie Breaking Example — scikit-learn 1...
C = 1 , break_ties = break_ties...scatter ( X [:, 0 ], X [:, 1 ], c = y , cmap = "Accent"...scikit-learn.org/stable/auto_examples/svm/plot_svm_tie_breaking.html -
1.9. Naive Bayes — scikit-learn 1.8.0 doc...
to class \(c\) , \(N_{c} = |\{ j \in J\mid y_j = c\}|\) is the...\sum_{j:y_j \neq c} d_{ij}} {\alpha + \sum_{j:y_j \neq c} \sum_{k} d_{kj}}\\w_{ci}...scikit-learn.org/stable/modules/naive_bayes.html -
Evaluate the performance of a classifier with C...
the regularization parameter C was not the best. In real life...model that is too regularized (C too low) to see # the impact on...scikit-learn.org/stable/auto_examples/model_selection/plot_confusion_matrix.html -
Plot multi-class SGD on the iris dataset —...
x0 * coef [ c , 0 ]) - intercept [ c ]) / coef [ c , 1 ] plt ....X [ idx , 0 ], X [ idx , 1 ], c = color , label = iris . target_names...scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_iris.html -
Gaussian Mixture Model Ellipsoids — sciki...
"c" , "cornflowerblue"...components np . random . seed ( 0 ) C = np . array ([[ 0.0 , - 0.1 ],...scikit-learn.org/stable/auto_examples/mixture/plot_gmm.html -
Demo of OPTICS clustering algorithm — sci...
"c." ] for klass , color in..."b." , "y." , "c." ] for klass , color in...scikit-learn.org/stable/auto_examples/cluster/plot_optics.html -
l1_min_c — scikit-learn 1.8.0 documentation
for C . The lower bound for C is computed such that for C in (l1_min_C,...l1_min_c float Minimum value for C. Examples >>> from sklearn.svm...scikit-learn.org/stable/modules/generated/sklearn.svm.l1_min_c.html -
Importance of Feature Scaling — scikit-le...
) Optimal C for the unscaled PCA: 0.0004 Optimal C for the standardized...], X_plot [ "hue" ], c = y , s = 20 , edgecolor = "k"...scikit-learn.org/stable/auto_examples/preprocessing/plot_scaling_importance.html -
clustering.rst.txt
- \frac{H(C|K)}{H(C)} .. math:: c = 1 - \frac{H(K|C)}{H(K)} where...math:: H(C|K) = - \sum_{c=1}^{|C|} \sum_{k=1}^{|K|} \frac{n_{c,k}}{n}...scikit-learn.org/stable/_sources/modules/clustering.rst.txt