smplmark

OpenML-CC18: Internet-Advertisements

Best predictive accuracy per machine-learning flow on the Internet-Advertisements classification task from the OpenML-CC18 suite.

Community results for the Internet-Advertisements classification task from OpenML-CC18, OpenML's curated suite of 72 classification tasks (www.openml.org/t/167125). Each target is a flow — a specific algorithm or pipeline — shown with the best predictive accuracy recorded for it on this task in OpenML's public evaluation listing, under the task's fixed estimation procedure.

Metrics

  • predictive_accuracy

Targets (15)

  • mlr.classif.rpart(47)
  • sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(4)
  • sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,encoder=sklearn.preprocessing._encoders.OneHotEncoder,model=sklearn.tree._classes.DecisionTreeClassifier)(2)
  • sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,histgradientboostingclassifier=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(1)
  • sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,svc=sklearn.svm.classes.SVC)(1)
  • sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,fkceigenpro=sklearn_extra.fast_kernel.FKCEigenPro)(1)
  • sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,fkc_eigenpro=sklearn_extra.fast_kernel.FKC_EigenPro)(1)
  • sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1)
  • weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.RBFKernel,weka.classifiers.functions.Logistic)(1)
  • weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)(3)
  • weka.classifiers.meta.MultiSearch(weka.classifiers.meta.multisearch.RandomSearch,weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingVa…
  • weka.classifiers.meta.MultiSearch(weka.classifiers.meta.multisearch.RandomSearch,weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingVa…
  • weka.classifiers.meta.MultiSearch(weka.classifiers.meta.multisearch.RandomSearch,weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingVa…
  • weka.classifiers.trees.J48(1)
  • weka.classifiers.trees.RandomForest(1)

Published by OpenML.