OpenML
An implementation of the evaluation measure "EuclideanDistance"
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An implementation of the evaluation measure "PolynomialKernel"
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An implementation of the evaluation measure "RBFKernel"
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An implementation of the evaluation measure "area_under_roc_curve"
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An implementation of the evaluation measure "average_cost"
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An implementation of the evaluation measure "build_cpu_time"
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An implementation of the evaluation measure "build_memory"
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An implementation of the evaluation measure "class_complexity"
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An implementation of the evaluation measure "class_complexity_gain"
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An implementation of the evaluation measure "confusion_matrix"
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An implementation of the evaluation measure "correlation_coefficient"
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An implementation of the evaluation measure "f_measure"
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An implementation of the evaluation measure "kappa"
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An implementation of the evaluation measure "kb_relative_information_score"
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An implementation of the evaluation measure "kohavi_wolpert_bias_squared"
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An implementation of the evaluation measure "kohavi_wolpert_error"
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An implementation of the evaluation measure "kohavi_wolpert_sigma_squared"
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An implementation of the evaluation measure "kohavi_wolpert_variance"
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An implementation of the evaluation measure "kononenko_bratko_information_score"
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An implementation of the evaluation measure "matthews_correlation_coefficient"
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An implementation of the evaluation measure "mean_absolute_error"
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An implementation of the evaluation measure "mean_class_complexity"
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An implementation of the evaluation measure "mean_class_complexity_gain"
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An implementation of the evaluation measure "mean_f_measure"
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An implementation of the evaluation measure "mean_kononenko_bratko_information_score"
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An implementation of the evaluation measure "mean_precision"
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An implementation of the evaluation measure "mean_prior_absolute_error"
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An implementation of the evaluation measure "mean_prior_class_complexity"
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An implementation of the evaluation measure "mean_recall"
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An implementation of the evaluation measure "mean_weighted_area_under_roc_curve"
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An implementation of the evaluation measure "mean_weighted_f_measure"
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An implementation of the evaluation measure "mean_weighted_precision"
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An implementation of the evaluation measure "mean_weighted_recall"
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An implementation of the evaluation measure "number_of_instances"
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An implementation of the evaluation measure "precision"
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An implementation of the evaluation measure "predictive_accuracy"
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An implementation of the evaluation measure "prior_class_complexity"
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An implementation of the evaluation measure "prior_entropy"
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An implementation of the evaluation measure "recall"
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An implementation of the evaluation measure "relative_absolute_error"
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An implementation of the evaluation measure "root_mean_prior_squared_error"
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An implementation of the evaluation measure "root_mean_squared_error"
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An implementation of the evaluation measure "root_relative_squared_error"
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An implementation of the evaluation measure "run_cpu_time"
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An implementation of the evaluation measure "run_memory"
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An implementation of the evaluation measure "run_virtual_memory"
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An implementation of the evaluation measure "single_point_area_under_roc_curve"
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An implementation of the evaluation measure "total_cost"
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An implementation of the evaluation measure "unclassified_instance_count"
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An implementation of the evaluation measure "webb_bias"
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An implementation of the evaluation measure "webb_error"
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An implementation of the evaluation measure "webb_variance"
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Default information about OS, JVM, installations, etc.
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Every GB of RAM deployed for 1 hour equals one RAM-Hour.
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Information of the CPU performance on which the run was performed
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Weka implementation of ZeroR
232 runs0 likes4 downloads4 reach200 impact
R.C. Holte (1993). Very simple classification rules perform well on most commonly used datasets. Machine Learning. 11:63-91.
397 runs0 likes3 downloads3 reach360 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.
127 runs0 likes3 downloads3 reach105 impact
William W. Cohen: Fast Effective Rule Induction. In: Twelfth International Conference on Machine Learning, 115-123, 1995.
126 runs0 likes3 downloads3 reach95 impact
Ross Quinlan (1993). C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo, CA.
1717 runs0 likes3 downloads3 reach1691 impact
Weka implementation of REPTree
932 runs0 likes11 downloads11 reach894 impact
Weka implementation of DecisionStump
126 runs0 likes3 downloads3 reach97 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
Weka implementation of RandomTree
128 runs0 likes3 downloads3 reach100 impact
Leo Breiman (2001). Random Forests. Machine Learning. 45(1):5-32.
389 runs1 likes20 downloads21 reach360 impact
D. Aha, D. Kibler (1991). Instance-based learning algorithms. Machine Learning. 6:37-66.
775 runs0 likes3 downloads3 reach747 impact
Weka implementation of BayesNet
252 runs0 likes7 downloads7 reach222 impact
G.F. Cooper, E. Herskovits (1990). A Bayesian method for constructing Bayesian belief networks from databases. G. Cooper, E. Herskovits (1992). A Bayesian method for the induction of probabilistic…
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Weka implementation of SGD
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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,…
868 runs0 likes3 downloads3 reach831 impact
Weka implementation of PolyKernel
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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,…
1833 runs0 likes3 downloads3 reach1805 impact
Weka implementation of RBFKernel
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le Cessie, S., van Houwelingen, J.C. (1992). Ridge Estimators in Logistic Regression. Applied Statistics. 41(1):191-201.
124 runs0 likes3 downloads3 reach94 impact
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
341 runs0 likes3 downloads3 reach316 impact
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
630 runs0 likes3 downloads3 reach598 impact
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
339 runs0 likes3 downloads3 reach309 impact
Moa implementation of NaiveBayes
291 runs0 likes14 downloads14 reach78 impact
Moa implementation of SGD
417 runs0 likes2 downloads2 reach41 impact
A Hoeffding tree (VFDT) is an incremental, anytime decision tree induction algorithm that is capable of learning from massive data streams, assuming that the distribution generating examples does not…
270 runs0 likes8 downloads8 reach53 impact
Moa implementation of kNN
258 runs0 likes3 downloads3 reach41 impact
Moa implementation of LeveragingBag
280 runs0 likes2 downloads2 reach41 impact
Moa implementation of LeveragingBag
260 runs0 likes2 downloads2 reach40 impact
Moa implementation of OzaBag
257 runs0 likes4 downloads4 reach54 impact
Moa implementation of OzaBagAdwin
199 runs0 likes3 downloads3 reach42 impact
Moa implementation of OzaBoost
252 runs0 likes4 downloads4 reach46 impact
Moa implementation of OzaBoostAdwin
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Moa implementation of AMRules
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Moa implementation of RandomRules
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Moa implementation of Perceptron
337 runs0 likes3 downloads3 reach49 impact
Moa implementation of RuleClassifier
194 runs0 likes2 downloads2 reach39 impact
Moa implementation of ASHoeffdingTree
246 runs0 likes2 downloads2 reach45 impact
Moa implementation of FIMTDD
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Moa implementation of HoeffdingAdaptiveTree
262 runs0 likes8 downloads8 reach48 impact
Moa implementation of RandomHoeffdingTree
245 runs0 likes4 downloads4 reach39 impact
Moa implementation of NoChange
245 runs0 likes2 downloads2 reach44 impact
Moa implementation of MajorityClass
246 runs0 likes2 downloads2 reach48 impact
Moa implementation of SPegasos
245 runs0 likes2 downloads2 reach36 impact
Moa implementation of WEKAClassifier
301 runs0 likes2 downloads2 reach42 impact
Ross Quinlan (1993). C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo, CA.
8 runs0 likes3 downloads3 reach7 impact