Flow generated by run_task
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Automatically created sub-component.
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Automatically created sub-component.
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Automatically created sub-component.
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Automatically created sub-component.
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Automatically created sub-component.
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Automatically created sub-component.
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Automatically created sub-component.
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Automatically created sub-component.
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Automatically created sub-component.
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Code to run H2O through MLR. https://github.com/meta-QSAR/rmetaqsar/blob/master/fnc-deeplrn.R
2556 runs0 likes1 downloads1 reach2556 impact
Flow generated by run_task
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Learner mlr.classif.randomForest from package(s) randomForest.
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Learner mlr.classif.rpart from package(s) rpart.
26 runs0 likes0 downloads0 reach4 impact
Learner mlr.classif.randomForest from package(s) randomForest.
21 runs0 likes0 downloads0 reach5 impact
Automatically created sub-component.
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Automatically created sub-component.
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Weka implementation of FilteredClassifier
1 runs0 likes0 downloads0 reach0 impact
Leo Breiman (2001). Random Forests. Machine Learning. 45(1):5-32.
12 runs0 likes0 downloads0 reach12 impact
Weka implementation of CostSensitiveClassifier
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Weka implementation of FilteredClassifier
9 runs0 likes0 downloads0 reach8 impact
Automatically created sub-component.
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Flow generated by run_task
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Learner mlr.classif.rpart from package(s) rpart.
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Learner mlr.classif.randomForest from package(s) randomForest.
2 runs0 likes0 downloads0 reach0 impact
Automatically created sub-component.
119 runs0 likes0 downloads0 reach64 impact
Automatically created sub-component.
45 runs0 likes1 downloads1 reach35 impact
Automatically created sub-component.
0 runs0 likes0 downloads0 reach0 impact
Ross Quinlan (1993). C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo, CA.
462 runs0 likes0 downloads0 reach448 impact
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
4 runs0 likes0 downloads0 reach1 impact
Weka implementation of DecisionStump
17 runs0 likes0 downloads0 reach17 impact
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
Automatically created scikit-learn flow.
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Automatically created scikit-learn flow.
4 runs0 likes0 downloads0 reach2 impact
Automatically created scikit-learn flow.
6 runs0 likes0 downloads0 reach0 impact
Automatically created scikit-learn flow.
3 runs0 likes0 downloads0 reach0 impact
Automatically created scikit-learn flow.
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Automatically created scikit-learn flow.
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Weka implementation of REPTree
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Weka implementation of REPTree
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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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Andrew Mccallum, Kamal Nigam: A Comparison of Event Models for Naive Bayes Text Classification. In: AAAI-98 Workshop on 'Learning for Text Categorization', 1998.
34 runs0 likes1 downloads1 reach0 impact
George H. John, Pat Langley: Estimating Continuous Distributions in Bayesian Classifiers. In: Eleventh Conference on Uncertainty in Artificial Intelligence, San Mateo, 338-345, 1995.
59 runs0 likes1 downloads1 reach0 impact
David J.C. Mackay (1998). Introduction to Gaussian Processes. Dept. of Physics, Cambridge University, UK.
17 runs0 likes1 downloads1 reach0 impact
Weka implementation of LinearRegression
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Weka implementation of MultilayerPerceptron
178 runs0 likes1 downloads1 reach0 impact
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…
57 runs0 likes1 downloads1 reach0 impact
S.K. Shevade, S.S. Keerthi, C. Bhattacharyya, K.R.K. Murthy: Improvements to the SMO Algorithm for SVM Regression. In: IEEE Transactions on Neural Networks, 1999. S.K. Shevade, S.S. Keerthi, C.…
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Y. Freund, R. E. Schapire: Large margin classification using the perceptron algorithm. In: 11th Annual Conference on Computational Learning Theory, New York, NY, 209-217, 1998.
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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.
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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…
56 runs0 likes1 downloads1 reach0 impact
J.H. Friedman (1999). Stochastic Gradient Boosting.
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Weka implementation of AttributeSelectedClassifier
98 runs0 likes1 downloads1 reach0 impact
M. A. Hall (1998). Correlation-based Feature Subset Selection for Machine Learning. Hamilton, New Zealand.
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Weka implementation of BestFirst
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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.
53 runs0 likes1 downloads1 reach0 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…
25 runs0 likes1 downloads1 reach0 impact
R. Kohavi (1995). Wrappers for Performance Enhancement and Oblivious Decision Graphs. Department of Computer Science, Stanford University.
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Weka implementation of FilteredClassifier
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Usama M. Fayyad, Keki B. Irani: Multi-interval discretization of continuousvalued attributes for classification learning. In: Thirteenth International Joint Conference on Articial Intelligence,…
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Weka implementation of MultiClassClassifier
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Weka implementation of MultiClassClassifierUpdateable
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Weka implementation of MultiScheme
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Weka implementation of RandomCommittee
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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
Ron Kohavi: The Power of Decision Tables. In: 8th European Conference on Machine Learning, 174-189, 1995.
54 runs0 likes1 downloads1 reach0 impact
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…
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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.
58 runs0 likes1 downloads1 reach0 impact
Niels Landwehr, Mark Hall, Eibe Frank (2005). Logistic Model Trees. Machine Learning. 95(1-2):161-205. Marc Sumner, Eibe Frank, Mark Hall: Speeding up Logistic Model Tree Induction. In: 9th European…
284 runs0 likes2 downloads2 reach0 impact
David J.C. Mackay (1998). Introduction to Gaussian Processes. Dept. of Physics, Cambridge University, UK.
28 runs0 likes1 downloads1 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
98 runs0 likes1 downloads1 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
97 runs0 likes1 downloads1 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
97 runs0 likes1 downloads1 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
113 runs0 likes1 downloads1 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
106 runs0 likes1 downloads1 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
112 runs0 likes1 downloads1 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
97 runs0 likes1 downloads1 reach0 impact
Haijian Shi (2007). Best-first decision tree learning. Hamilton, NZ. Jerome Friedman, Trevor Hastie, Robert Tibshirani (2000). Additive logistic regression : A statistical view of boosting. Annals of…
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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.
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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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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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
96 runs0 likes1 downloads1 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
105 runs0 likes1 downloads1 reach0 impact
Alexander Genkin, David D. Lewis, David Madigan (2004). Large-scale bayesian logistic regression for text categorization. URL http://www.stat.rutgers.edu/~madigan/PAPERS/shortFat-v3a.pdf.
3 runs0 likes2 downloads2 reach2 impact
H. Zhang, L. Jiang, J. Su: Hidden Naive Bayes. In: Twentieth National Conference on Artificial Intelligence, 919-924, 2005.
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David J.C. Mackay (1998). Introduction to Gaussian Processes. Dept. of Physics, Cambridge University, UK.
0 runs0 likes0 downloads0 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
117 runs0 likes1 downloads1 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
105 runs0 likes1 downloads1 reach0 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,…
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S. Shalev-Shwartz, Y. Singer, N. Srebro: Pegasos: Primal Estimated sub-GrAdient SOlver for SVM. In: 24th International Conference on MachineLearning, 807-814, 2007.
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
112 runs0 likes1 downloads1 reach0 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
112 runs0 likes1 downloads1 reach0 impact
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
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Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
114 runs0 likes1 downloads1 reach0 impact
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
120 runs0 likes2 downloads2 reach0 impact
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
99 runs0 likes1 downloads1 reach0 impact
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
112 runs0 likes1 downloads1 reach0 impact
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
94 runs0 likes1 downloads1 reach0 impact
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
103 runs0 likes1 downloads1 reach0 impact