OpenML
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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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…
19 runs0 likes0 downloads0 reach0 impact
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…
19 runs0 likes0 downloads0 reach0 impact
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…
19 runs0 likes0 downloads0 reach0 impact
Weka implementation of ZeroR
19 runs0 likes1 downloads1 reach17 impact
A random forest classifier. A random forest is a meta estimator that fits a number of decision tree classifiers on various sub-samples of the dataset and use averaging to improve the predictive…
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Tuned Random Forest baseline as set up by the AutoML BenchmarkSource: source: https://github.com/openml/automlbenchmark/releases/tag/v0.9
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Random Forest baseline as set up by the AutoML BenchmarkSource: source: https://github.com/openml/automlbenchmark/releases/tag/v0.9
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Learner classif.logreg from package(s) stats.
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Flow generated by openml_run
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Learner mlr.classif.logreg from package(s) stats.
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Jason D. Rennie, Lawrence Shih, Jaime Teevan, David R. Karger: Tackling the Poor Assumptions of Naive Bayes Text Classifiers. In: ICML, 616-623, 2003.
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Weka implementation of IsotonicRegression
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Weka implementation of AttributeSelectedClassifier
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Weka implementation of AttributeSelectedClassifier
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Weka implementation of AttributeSelectedClassifier
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Weka implementation of ConjunctiveRule
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Weka implementation of AttributeSelectedClassifier
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Automatically created scikit-learn flow.
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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…
18 runs0 likes0 downloads0 reach0 impact
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…
18 runs0 likes0 downloads0 reach0 impact
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…
18 runs0 likes0 downloads0 reach0 impact
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…
18 runs0 likes0 downloads0 reach0 impact
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…
18 runs0 likes0 downloads0 reach0 impact
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…
18 runs0 likes0 downloads0 reach0 impact
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…
18 runs0 likes0 downloads0 reach0 impact
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…
18 runs0 likes0 downloads0 reach0 impact
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…
18 runs0 likes0 downloads0 reach0 impact
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…
18 runs0 likes0 downloads0 reach0 impact
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…
18 runs0 likes0 downloads0 reach0 impact
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…
18 runs0 likes0 downloads0 reach0 impact
A decision tree classifier.
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C-Support Vector Classification. The implementation is based on libsvm. The fit time complexity is more than quadratic with the number of samples which makes it hard to scale to dataset with more than…
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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…
18 runs0 likes0 downloads0 reach0 impact
H2O AutoML 3.24.0.1 as set up by the AutoML BenchmarkSource: source: https://github.com/openml/automlbenchmark/releases/tag/v0.9
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TPOT as set up by the AutoML BenchmarkSource: source: https://github.com/openml/automlbenchmark/releases/tag/v0.9
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Learner ModelMultiplexer from package(s) e1071, ada, randomForest.
17 runs0 likes1 downloads1 reach0 impact
Learner classif.bartMachine from package(s) bartMachine.
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Learner classif.knn from package(s) class.
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Learner classif.rotationForest from package(s) rotationForest.
17 runs0 likes1 downloads1 reach0 impact
Learner classif.sda from package(s) sda.
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Learner mlr.classif.J48 from package(s) RWeka.
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Weka implementation of DecisionStump
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David J.C. Mackay (1998). Introduction to Gaussian Processes. Dept. of Physics, Cambridge University, UK.
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Geoffrey Holmes, Bernhard Pfahringer, Richard Kirkby, Eibe Frank, Mark Hall: Multiclass alternating decision trees. In: ECML, 161-172, 2001.
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Eibe Frank, Mark Hall, Bernhard Pfahringer: Locally Weighted Naive Bayes. In: 19th Conference in Uncertainty in Artificial Intelligence, 249-256, 2003. C. Atkeson, A. Moore, S. Schaal (1996). Locally…
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Weka implementation of AttributeSelectedClassifier
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R. Quinlan (1986). Induction of decision trees. Machine Learning. 1(1):81-106.
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Automatically created scikit-learn flow.
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Weka implementation of FilteredClassifier
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Weka implementation of FilteredClassifier
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Weka implementation of RandomizableFilteredClassifier
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A flow using decisionStump for the POC.
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Automatically created scikit-learn flow.
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Automatically created scikit-learn flow.
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
17 runs0 likes2 downloads2 reach9 impact
Learner classif.cforest from package(s) party.
17 runs0 likes1 downloads1 reach0 impact
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…
17 runs0 likes0 downloads0 reach0 impact
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…
17 runs0 likes0 downloads0 reach0 impact
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…
17 runs0 likes0 downloads0 reach0 impact
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…
17 runs0 likes0 downloads0 reach0 impact
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…
17 runs0 likes0 downloads0 reach0 impact
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…
17 runs0 likes0 downloads0 reach0 impact
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…
17 runs0 likes0 downloads0 reach0 impact
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…
17 runs0 likes0 downloads0 reach0 impact
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…
17 runs0 likes0 downloads0 reach0 impact
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…
17 runs0 likes0 downloads0 reach0 impact
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…
17 runs0 likes0 downloads0 reach0 impact
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…
17 runs0 likes0 downloads0 reach0 impact
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…
17 runs0 likes0 downloads0 reach0 impact
Auto-WEKA 2.6 as set up by the AutoML BenchmarkSource: source: https://github.com/openml/automlbenchmark/releases/tag/v0.9
17 runs0 likes1 downloads1 reach0 impact
Learner classif.glmboost from package(s) mboost.
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D. Aha, D. Kibler (1991). Instance-based learning algorithms. Machine Learning. 6:37-66.
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Weka implementation of FilteredClassifier
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Automatically created sub-component.
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Niels Landwehr, Mark Hall, Eibe Frank (2005). Logistic Model Trees. Marc Sumner, Eibe Frank, Mark Hall: Speeding up Logistic Model Tree Induction. In: 9th European Conference on Principles and…
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William W. Cohen: Fast Effective Rule Induction. In: Twelfth International Conference on Machine Learning, 115-123, 1995.
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Moa implementation of RandomRules
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Weka implementation of AttributeSelectedClassifier
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Weka implementation of ClassificationViaClustering
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A flow using hyperpipes for the POC.
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Learner mlr.classif.naiveBayes from package(s) e1071.
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Learner classif.xgboost from package(s) xgboost.
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A flow using j48 for the POC.
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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…
16 runs0 likes0 downloads0 reach0 impact
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…
16 runs0 likes0 downloads0 reach0 impact
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…
16 runs0 likes0 downloads0 reach0 impact
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…
16 runs0 likes0 downloads0 reach0 impact
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…
16 runs0 likes0 downloads0 reach0 impact
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…
16 runs0 likes0 downloads0 reach0 impact
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…
16 runs0 likes0 downloads0 reach0 impact
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…
16 runs0 likes0 downloads0 reach0 impact