Weka implementation of CostSensitiveClassifier
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E. Frank, Y. Wang, S. Inglis, G. Holmes, I.H. Witten (1998). Using model trees for classification. Machine Learning. 32(1):63-76.
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Moa implementation of StackingAttempt
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Moa implementation of StackingAttemptV2
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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.glmnet from package(s) glmnet.
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Learner classif.IBk from package(s) RWeka.
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Automatically created scikit-learn flow.
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Automatically created scikit-learn flow.
52 runs0 likes0 downloads0 reach52 impact
R. Kohavi (1995). Wrappers for Performance Enhancement and Oblivious Decision Graphs. Department of Computer Science, Stanford University.
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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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Ludmila I. Kuncheva (2004). Combining Pattern Classifiers: Methods and Algorithms. John Wiley and Sons, Inc.. J. Kittler, M. Hatef, Robert P.W. Duin, J. Matas (1998). On combining classifiers. IEEE…
52 runs0 likes1 downloads1 reach0 impact
Moa implementation of StackingAttemptV2
52 runs0 likes2 downloads2 reach33 impact
keras.wrappers.scikit_learn.KerasClassifier(Reshape,Conv2D,Conv2D,MaxPooling2D,BatchNormalization,Conv2D,Conv2D,MaxPooling2D,BatchNormalization,Conv2D,Conv2D,Conv2D,MaxPooling2D,BatchNormalization,Flatten,Dense,Dropout,Dense,Dropout,Dense) (1)
Automatically created scikit-learn flow.
52 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…
52 runs0 likes0 downloads0 reach0 impact
Learner classif.nnTrain from package(s) deepnet.
51 runs0 likes1 downloads1 reach0 impact
Flow generated by run_task
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Learner mlr.classif.lda.preproc from package(s) MASS.
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Weka implementation of AttributeSelectedClassifier
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Weka implementation of MultiClassClassifier
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le Cessie, S., van Houwelingen, J.C. (1992). Ridge Estimators in Logistic Regression. Applied Statistics. 41(1):191-201.
51 runs0 likes1 downloads1 reach0 impact
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
51 runs0 likes2 downloads2 reach46 impact
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
51 runs0 likes2 downloads2 reach46 impact
Moa implementation of StackingAttemptV2
51 runs0 likes2 downloads2 reach11 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…
51 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…
51 runs0 likes0 downloads0 reach0 impact
Weka implementation of FilteredClassifier
50 runs0 likes0 downloads0 reach49 impact
Learner mlr.classif.cforest.preproc from package(s) party.
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Learner mlr.classif.multinom.preproc from package(s) nnet.
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John G. Cleary, Leonard E. Trigg: K*: An Instance-based Learner Using an Entropic Distance Measure. In: 12th International Conference on Machine Learning, 108-114, 1995.
50 runs0 likes2 downloads2 reach37 impact
Ron Kohavi: Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid. In: Second International Conference on Knoledge Discovery and Data Mining, 202-207, 1996.
50 runs0 likes2 downloads2 reach45 impact
Learner classif.randomForest from package(s) randomForest.
50 runs0 likes2 downloads2 reach5 impact
Webb, Geoffrey I., Boughton, Janice, Zheng, Fei, Ting, Kai Ming, Salem, Houssam (2012). Learning by extrapolation from marginal to full-multivariate probability distributions: decreasingly naive…
50 runs0 likes2 downloads2 reach1 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…
50 runs0 likes0 downloads0 reach0 impact
Automatically created scikit-learn flow.
50 runs0 likes0 downloads0 reach0 impact
Automatically created scikit-learn flow.
50 runs0 likes0 downloads0 reach33 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…
50 runs0 likes0 downloads0 reach0 impact
Learner classif.ranger from package(s) ranger.
49 runs0 likes1 downloads1 reach0 impact
Learner mlr.classif.rpart.preproc from package(s) rpart.
49 runs0 likes0 downloads0 reach0 impact
Moa implementation of LeveragingBag
49 runs0 likes1 downloads1 reach0 impact
Geoff Hulten, Laurie Spencer, Pedro Domingos: Mining time-changing data streams. In: ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, 97-106, 2001.
49 runs0 likes3 downloads3 reach37 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…
49 runs0 likes0 downloads0 reach0 impact
Automatically created scikit-learn flow.
49 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…
49 runs0 likes0 downloads0 reach0 impact
Learner classif.rpart from package(s) rpart.
48 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…
48 runs0 likes0 downloads0 reach46 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…
48 runs0 likes0 downloads0 reach0 impact
Automatically created scikit-learn flow.
48 runs0 likes0 downloads0 reach40 impact
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
47 runs0 likes0 downloads0 reach0 impact
Weka implementation of FilteredClassifier
47 runs0 likes0 downloads0 reach45 impact
Freund, Y., Mason, L.: The alternating decision tree learning algorithm. In: Proceeding of the Sixteenth International Conference on Machine Learning, Bled, Slovenia, 124-133, 1999.
47 runs0 likes2 downloads2 reach44 impact
Andrew Mccallum, Kamal Nigam: A Comparison of Event Models for Naive Bayes Text Classification. In: AAAI-98 Workshop on 'Learning for Text Categorization', 1998.
47 runs0 likes7 downloads7 reach46 impact
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…
47 runs0 likes2 downloads2 reach32 impact
Moa implementation of AccuracyWeightedEnsemble
47 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…
47 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…
47 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…
47 runs0 likes0 downloads0 reach0 impact
Learner classif.ada from package(s) ada.
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Learner classif.svm from package(s) e1071.
46 runs0 likes1 downloads1 reach0 impact
Learner classif.glmnet from package(s) glmnet.
46 runs0 likes1 downloads1 reach0 impact
Learner classif.kknn from package(s) !kknn.
46 runs0 likes1 downloads1 reach0 impact
Automatically created scikit-learn flow.
46 runs0 likes0 downloads0 reach46 impact
Ross J. Quinlan: Learning with Continuous Classes. In: 5th Australian Joint Conference on Artificial Intelligence, Singapore, 343-348, 1992. Y. Wang, I. H. Witten: Induction of model trees for…
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N. Littlestone (1988). Learning quickly when irrelevant attributes are abound: A new linear threshold algorithm. Machine Learning. 2:285-318. N. Littlestone (1989). Mistake bounds and logarithmic…
46 runs0 likes2 downloads2 reach37 impact
J. Platt: Fast Training of Support Vector Machines using Sequential Minimal Optimization. In B. Schoelkopf and C. Burges and A. Smola, editors, Advances in Kernel Methods - Support Vector Learning,…
46 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…
46 runs0 likes0 downloads0 reach0 impact
Automatically created scikit-learn flow.
46 runs0 likes0 downloads0 reach25 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…
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Automatically created sub-component.
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Learner mlr.classif.ctree from package(s) party.
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Geoffrey Holmes, Mark Hall, Eibe Frank: Generating Rule Sets from Model Trees. In: Twelfth Australian Joint Conference on Artificial Intelligence, 1-12, 1999. Ross J. Quinlan: Learning with Continuous…
45 runs0 likes1 downloads1 reach45 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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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.
45 runs0 likes2 downloads2 reach33 impact
Moa implementation of AMRulesRegressor
45 runs0 likes2 downloads2 reach40 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…
45 runs0 likes1 downloads1 reach44 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…
45 runs0 likes0 downloads0 reach0 impact
Flow generated by run_task
44 runs0 likes2 downloads2 reach7 impact
Weka implementation of ZeroR
44 runs0 likes0 downloads0 reach43 impact
Weka implementation of FilteredClassifier
44 runs0 likes0 downloads0 reach43 impact
Mark Hall, Eibe Frank: Combining Naive Bayes and Decision Tables. In: Proceedings of the 21st Florida Artificial Intelligence Society Conference (FLAIRS), 318-319, 2008.
44 runs0 likes2 downloads2 reach32 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…
44 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…
44 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…
44 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…
44 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…
44 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…
44 runs0 likes0 downloads0 reach0 impact
Weka implementation of AttributeSelectedClassifier
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Weka implementation of FilteredClassifier
43 runs0 likes0 downloads0 reach42 impact
S. Shalev-Shwartz, Y. Singer, N. Srebro: Pegasos: Primal Estimated sub-GrAdient SOlver for SVM. In: 24th International Conference on MachineLearning, 807-814, 2007.
43 runs0 likes1 downloads1 reach0 impact
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…
43 runs0 likes2 downloads2 reach41 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…
43 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…
43 runs0 likes0 downloads0 reach0 impact
Weka implementation of RandomizableFilteredClassifier
43 runs0 likes0 downloads0 reach1 impact
Automatically created scikit-learn flow.
43 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…
43 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…
43 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…
43 runs0 likes0 downloads0 reach0 impact
Weka implementation of AttributeSelectedClassifier
42 runs0 likes0 downloads0 reach0 impact
Weka implementation of AttributeSelectedClassifier
42 runs0 likes0 downloads0 reach0 impact
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
42 runs0 likes0 downloads0 reach0 impact