OpenML
Weka implementation of AttributeSelectedClassifier
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Weka implementation of AttributeSelectedClassifier
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Moa implementation of ORTO
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Learner classif.mlp from package(s) RSNNS.
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Learner classif.ada from package(s) ada.
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Weka implementation of AttributeSelectedClassifier
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Flow generated by run_task
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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Weka implementation of CostSensitiveClassifier
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Learner classif.xyf from package(s) kohonen.
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Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
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J. Cendrowska (1987). PRISM: An algorithm for inducing modular rules. International Journal of Man-Machine Studies. 27(4):349-370.
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Weka implementation of FilteredClassifier
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Learner classif.mda from package(s) !mda.
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Learner classif.LiblineaRL2LogReg from package(s) LiblineaR.
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Learner classif.nnTrain from package(s) deepnet.
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Weka implementation of AttributeSelectedClassifier
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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Learner classif.bdk from package(s) kohonen.
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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Automatically created scikit-learn flow.
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Learner classif.saeDNN from package(s) deepnet.
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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Learner classif.dbnDNN from package(s) deepnet.
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Learner classif.sda from package(s) sda.
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Learner mlr.classif.naiveBayes.preproc from package(s) e1071.
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Please use the mlr add-on code https://github.com/HeidiSeibold/sandbox/blob/master/rstuff/openml_newctree/new_ctree_mlr.R and devel partykit package revision 1118:…
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Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
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Weka implementation of ZeroR
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Weka implementation of FilteredClassifier
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Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
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Learner classif.rpart from package rpart.
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Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
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Learner mlr.classif.ctree from package(s) party.
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Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
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Weka implementation of KernelLogisticRegression
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Learner classif.logreg from package(s) stats.
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Learner classif.rotationForest from package(s) rotationForest.
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Automatically created scikit-learn flow.
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Learner mlr.classif.rpart from package(s) rpart.
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Weka implementation of RandomTree
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Learner classif.sparseLDA from package(s) !sparseLDA, MASS, !elasticnet.
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Weka implementation of FilteredClassifier
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Moa implementation of AccuracyWeightedEnsemble
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Learner classif.naiveBayes from package(s) e1071.
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R. Kohavi (1995). Wrappers for Performance Enhancement and Oblivious Decision Graphs. Department of Computer Science, Stanford University.
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Learner classif.probit from package(s) stats.
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Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
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Automatically created scikit-learn flow.
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Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
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Learner classif.lda from package(s) MASS.
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Weka implementation of MultilayerPerceptron
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Weka implementation of MultilayerPerceptron
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J. Friedman, T. Hastie, R. Tibshirani (2000). Additive Logistic Regression: a Statistical View of Boosting. Annals of Statistics. 95(2):337-407.
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Weka implementation of AttributeSelectedClassifier
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Learner mlr.classif.kknn.preproc.preproc.tuned from package(s) !kknn.
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Learner mlr.classif.featureless.preproc from package(s) mlr.
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Learner mlr.regr.rpart from package(s) rpart.
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Automatically created scikit-learn flow.
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Learner mlr.classif.naiveBayes.preproc from package(s) e1071.
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Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
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Learner mlr.regr.rpart.dummied from package(s) rpart.
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Learner classif.randomForest from package(s) randomForest.
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Please use the mlr add-on code and devel partykit package revision 1078: https://r-forge.r-project.org/scm/viewvc.php/pkg/devel/?root=partykit
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Learner mlr.classif.gbm.preproc from package(s) gbm.
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Moa implementation of AccuracyWeightedEnsemble
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le Cessie, S., van Houwelingen, J.C. (1992). Ridge Estimators in Logistic Regression. Applied Statistics. 41(1):191-201.
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Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
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Weka implementation of REPTree
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Tin Kam Ho (1998). The Random Subspace Method for Constructing Decision Forests. IEEE Transactions on Pattern Analysis and Machine Intelligence. 20(8):832-844. URL…
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Learner classif.JRip from package RWeka.
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Automatically created scikit-learn flow.
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Automatically created scikit-learn flow.
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Eibe Frank, Ian H. Witten: Generating Accurate Rule Sets Without Global Optimization. In: Fifteenth International Conference on Machine Learning, 144-151, 1998.
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Learner classif.glmboost from package(s) mboost.
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Automatically created scikit-learn flow.
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Learner classif.binomial from package(s) stats.
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Learner classif.blackboost from package(s) mboost, party.
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le Cessie, S., van Houwelingen, J.C. (1992). Ridge Estimators in Logistic Regression. Applied Statistics. 41(1):191-201.
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Moa implementation of OzaBag
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Learner classif.qda from package(s) MASS.
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Moa implementation of OzaBag
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Andrew Mccallum, Kamal Nigam: A Comparison of Event Models for Naive Bayes Text Classification. In: AAAI-98 Workshop on 'Learning for Text Categorization', 1998.
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Flow generated by run_task
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