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Feature discretization — scikit-learn 1.8.0 doc...
n_features = 2 , n_redundant = 0 , n_informative = 2 , random_state...GradientBoostingClas: 0.84 SVC: 0.84 dataset 2 --------- LogisticRegression:...scikit-learn.org/stable/auto_examples/preprocessing/plot_discretization_classification.html -
Build and deploy an IBM MQ app to AWS Cloud: Us...
Patterns GitHub under an Apache 2.0 license. Prerequisites To familiarize...Docker and Docker Compose, version 2.0 or higher. To deploy the application...developer.ibm.com/tutorials/mq-build-deploy-ibm-mq-app-to-aws-cloud/ -
ProxyCachingConfiguration (Spring Framework 7.0...
proxyBeanMethods =false) @Role (2) public class ProxyCachingConfigur...nternalCacheAdvisor") @Role (2) public BeanFactoryCacheOper...docs.spring.io/spring-framework/docs/current/javadoc-api/org/springframework/cache/annotation/Pro... -
StratifiedKFold — scikit-learn 1.8.0 docu...
2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ]]) >>>...n_splits = 2 ) >>> skf . get_n_splits () 2 >>>...scikit-learn.org/stable/modules/generated/sklearn.model_selection.StratifiedKFold.html -
decomposition.rst.txt
\frac{1}{2} ||X - Y||_{\mathrm{Fro}}^2 = \frac{1}{2} \sum_{i,j}...Y) = \frac{1}{2} ||X - Y||_{Fro}^2 = \frac{1}{2} \sum_{i,j} (X_{ij}...scikit-learn.org/stable/_sources/modules/decomposition.rst.txt -
SVM Tie Breaking Example — scikit-learn 1.8.0 d...
2 ), ( 1 , 2 )] line = np . linspace...fig , sub = plt . subplots ( 2 , 1 , figsize = ( 5 , 8 )) titles...scikit-learn.org/stable/auto_examples/svm/plot_svm_tie_breaking.html -
IsolationForest example — scikit-learn 1.8.0 do...
2 ) @ covariance + np . array ([ 2 , 2 ]) # general...randn ( n_samples , 2 ) + np . array ([ - 2 , - 2 ]) # spherical outliers...scikit-learn.org/stable/auto_examples/ensemble/plot_isolation_forest.html -
DBSCAN — scikit-learn 1.8.0 documentation
2 ], [ 2 , 2 ], [ 2 , 3 ], ... [ 8 , 7 ],...memory complexity of \(O({n}^2)\) , which can occur when the...scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html -
root_mean_squared_error — scikit-learn 1.8.0 do...
2 , 7 ] >>> y_pred = [ 2.5 , 0.0 , 2 , 8 ] >>> r...]] >>> y_pred = [[ 0 , 2 ],[ - 1 , 2 ],[ 8 , - 5 ]] >>> root_mean_squared_error...scikit-learn.org/stable/modules/generated/sklearn.metrics.root_mean_squared_error.html -
safe_sqr — scikit-learn 1.8.0 documentation
Returns : X ** 2 element wise square Return the...>>> safe_sqr ([ 1 , 2 , 3 ]) array([1, 4, 9]) On this...scikit-learn.org/stable/modules/generated/sklearn.utils.safe_sqr.html