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Compare Stochastic learning strategies for MLPC...
plot_args = [ { "c" : "red" , "linestyle" : "-" }, { "c" : "green"..."-" }, { "c" : "blue" , "linestyle" : "-" }, { "c" : "red" ,...scikit-learn.org/stable/auto_examples/neural_networks/plot_mlp_training_curves.html -
Elastic Observability Labs
Instrumentation Log Analytics Monitor your C++ Applications with Elastic APM...Opentelemetry CPP client to monitor C++ application within Elastic APM...www.elastic.co/observability-labs -
DBFlute : Migration : 0.8.6
*Javaのみ(C#はもともとない) ConditionBean.union(XxxCB) *Javaのみ(C#はもともとない)...す。 allcommon.BFinder *Javaのみ(C#はもともとない) allcommon.GenMetaData...dbflute.seasar.org/ja/oldmigration/migrate-085to086.html -
SVR — scikit-learn 1.7.0 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 -
Scalable learning with polynomial kernel approx...
svm import SVC ksvm = SVC ( C = 500.0 , kernel = "poly" , degree...], ], label = "Linear SVM" , c = "green" , marker = "^" , ) ax...scikit-learn.org/stable/auto_examples/kernel_approximation/plot_scalable_poly_kernels.html -
Selecting the number of clusters with silhouett...
c in enumerate ( centers ): ax2 . scatter ( c [ 0 ], c [ 1...= 30 , lw = 0 , alpha = 0.7 , c = colors , edgecolor = "k" ) #...scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_silhouette_analysis.html -
Comparing random forests and the multi-output m...
c = "c" , s = s , marker = "^" , alpha...y_test [:, 1 ], edgecolor = "k" , c = "navy" , s = s , marker = "s"...scikit-learn.org/stable/auto_examples/ensemble/plot_random_forest_regression_multioutput.html -
Classification of text documents using sparse f...
name in ( ( LogisticRegression ( C = 5 , max_iter = 1000 ), "Logistic...penalty Linear SVC ( LinearSVC ( C = 0.1 , dual = False , max_iter...scikit-learn.org/stable/auto_examples/text/plot_document_classification_20newsgroups.html -
7.1. Pipelines and composite estimators — sciki...
set_params ( clf__C = 10 ) Pipeline(steps=[('reduce_dim',...ce_dim', PCA()), ('clf', SVC(C=10))]) When does it matter? #...scikit-learn.org/stable/modules/compose.html -
PLSSVD — scikit-learn 1.7.0 documentation
) >>> X_c , y_c = pls . transform ( X , y ) >>> X_c . shape ,..., y_c . shape ((4, 2), (4, 2)) fit ( X , y ) [source] # Fit model...scikit-learn.org/stable/modules/generated/sklearn.cross_decomposition.PLSSVD.html