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weka.SMO_PolyKernel (2)
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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weka.PolyKernel (2)
Weka implementation of PolyKernel
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weka.REPTree (3)
Weka implementation of REPTree
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weka.REPTree (4)
Weka implementation of REPTree
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weka.LinearRegression (2)
Weka implementation of LinearRegression
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weka.RegSMOImproved (1)
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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weka.VotedPerceptron (1)
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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weka.AdditiveRegression_DecisionStump (1)
J.H. Friedman (1999). Stochastic Gradient Boosting.
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weka.CfsSubsetEval (1)
M. A. Hall (1998). Correlation-based Feature Subset Selection for Machine Learning. Hamilton, New Zealand.
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weka.BestFirst (1)
Weka implementation of BestFirst
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weka.Discretize (1)
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.HNB (1)
H. Zhang, L. Jiang, J. Su: Hidden Naive Bayes. In: Twentieth National Conference on Artificial Intelligence, 919-924, 2005.
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weka.GaussianProcesses_PolyKernel (2)
David J.C. Mackay (1998). Introduction to Gaussian Processes. Dept. of Physics, Cambridge University, UK.
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weka.SMO_PolyKernel (5)
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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weka.GeneticSearch (1)
Weka implementation of GeneticSearch
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weka.HillClimber (1)
Weka implementation of HillClimber
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weka.LAGDHillClimber (1)
Weka implementation of LAGDHillClimber
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weka.RepeatedHillClimber (1)
Weka implementation of RepeatedHillClimber
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weka.SimulatedAnnealing (1)
R.R. Bouckaert (1995). Bayesian Belief Networks: from Construction to Inference. Utrecht, Netherlands.
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weka.TabuSearch (1)
R.R. Bouckaert (1995). Bayesian Belief Networks: from Construction to Inference. Utrecht, Netherlands.
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weka.TAN (1)
N. Friedman, D. Geiger, M. Goldszmidt (1997). Bayesian network classifiers. Machine Learning. 29(2-3):131-163.
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weka.PrincipalComponents (1)
Weka implementation of PrincipalComponents
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weka.NormalizedPolyKernel (1)
Weka implementation of NormalizedPolyKernel
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weka.PrecomputedKernelMatrixKernel (1)
Weka implementation of PrecomputedKernelMatrixKernel
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weka.Puk (1)
B. Uestuen, W.J. Melssen, L.M.C. Buydens (2006). Facilitating the application of Support Vector Regression by using a universal Pearson VII function based kernel. Chemometrics and Intelligent…
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weka.StringKernel (1)
Huma Lodhi, Craig Saunders, John Shawe-Taylor, Nello Cristianini, Christopher J. C. H. Watkins (2002). Text Classification using String Kernels. Journal of Machine Learning Research. 2:419-444. F.…
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weka.PLSFilter (1)
Tormod Naes, Tomas Isaksson, Tom Fearn, Tony Davies (2002). A User Friendly Guide to Multivariate Calibration and Classification. NIR Publications. StatSoft, Inc.. Partial Least Squares (PLS). Bent…
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weka.MLPClassifier (1)
Weka implementation of MLPClassifier
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weka.PLSClassifier_PLSFilter (2)
Weka implementation of PLSClassifier
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weka.RotationForest_PrincipalComponents_J48 (2)
Juan J. Rodriguez, Ludmila I. Kuncheva, Carlos J. Alonso (2006). Rotation Forest: A new classifier ensemble method. IEEE Transactions on Pattern Analysis and Machine Intelligence. 28(10):1619-1630.…
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weka.DecisionTable_BestFirst (2)
Ron Kohavi: The Power of Decision Tables. In: 8th European Conference on Machine Learning, 174-189, 1995.
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weka.MODLEM (1)
Jerzy Stefanowski: The rough set based rule induction technique for classification problems. In: 6th European Congress on Intelligent Techniques and Soft Computing, 109-113, 1998.
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weka.SimpleKMeans_EuclideanDistance (1)
D. Arthur, S. Vassilvitskii: k-means++: the advantages of carefull seeding. In: Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms, 1027-1035, 2007.
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weka.EuclideanDistance (1)
Wikipedia. Euclidean distance. URL http://en.wikipedia.org/wiki/Euclidean_distance.
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weka.ND_J48 (1)
Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems. In: PKDD, 84-95, 2005. Eibe Frank, Stefan Kramer: Ensembles of nested dichotomies for…
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classif.kknn (1)
Learner classif.kknn from package kknn.
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weka.K2 (2)
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.PolyKernel (4)
Weka implementation of PolyKernel
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weka.RBFKernel (2)
Weka implementation of RBFKernel
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weka.GaussianProcesses_PolyKernel (3)
David J.C. Mackay (1998). Introduction to Gaussian Processes. Dept. of Physics, Cambridge University, UK.
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weka.HNB (2)
H. Zhang, L. Jiang, J. Su: Hidden Naive Bayes. In: Twentieth National Conference on Artificial Intelligence, 919-924, 2005.
0 runs0 likes0 downloads0 reach0 impact
weka.LinearRegression (3)
Weka implementation of LinearRegression
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weka.SMO_PolyKernel (7)
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,…
0 runs0 likes0 downloads0 reach0 impact
weka.CfsSubsetEval (2)
M. A. Hall (1998). Correlation-based Feature Subset Selection for Machine Learning. Hamilton, New Zealand.
0 runs0 likes0 downloads0 reach0 impact
weka.BestFirst (2)
Weka implementation of BestFirst
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weka.AdditiveRegression_DecisionStump (2)
J.H. Friedman (1999). Stochastic Gradient Boosting.
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weka.IsolationForest (2)
Fei Tony Liu, Kai Ming Ting, Zhi-Hua Zhou: Isolation Forest. In: ICDM, 413-422, 2008.
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weka.IsotonicRegression (2)
Weka implementation of IsotonicRegression
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weka.LBR (2)
Zijian Zheng, G. Webb (2000). Lazy Learning of Bayesian Rules. Machine Learning. 4(1):53-84.
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weka.LeastMedSq (2)
Peter J. Rousseeuw, Annick M. Leroy (1987). Robust regression and outlier detection. .
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weka.MLPClassifier (2)
Weka implementation of MLPClassifier
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weka.MODLEM (2)
Jerzy Stefanowski: The rough set based rule induction technique for classification problems. In: 6th European Congress on Intelligent Techniques and Soft Computing, 109-113, 1998.
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weka.PaceRegression (2)
Wang, Y (2000). A new approach to fitting linear models in high dimensional spaces. Hamilton, New Zealand. Wang, Y., Witten, I. H.: Modeling for optimal probability prediction. In: Proceedings of the…
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weka.PLSClassifier_PLSFilter (3)
Weka implementation of PLSClassifier
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weka.PLSFilter (2)
Tormod Naes, Tomas Isaksson, Tom Fearn, Tony Davies (2002). A User Friendly Guide to Multivariate Calibration and Classification. NIR Publications. StatSoft, Inc.. Partial Least Squares (PLS). Bent…
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weka.PrincipalComponents (2)
Weka implementation of PrincipalComponents
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weka.Winnow (2)
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…
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weka.GeneticSearch (2)
Weka implementation of GeneticSearch
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weka.HillClimber (2)
Weka implementation of HillClimber
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weka.LAGDHillClimber (2)
Weka implementation of LAGDHillClimber
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weka.RepeatedHillClimber (2)
Weka implementation of RepeatedHillClimber
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weka.SimulatedAnnealing (2)
R.R. Bouckaert (1995). Bayesian Belief Networks: from Construction to Inference. Utrecht, Netherlands.
0 runs0 likes0 downloads0 reach0 impact
weka.TabuSearch (2)
R.R. Bouckaert (1995). Bayesian Belief Networks: from Construction to Inference. Utrecht, Netherlands.
0 runs0 likes0 downloads0 reach0 impact
weka.TAN (2)
N. Friedman, D. Geiger, M. Goldszmidt (1997). Bayesian network classifiers. Machine Learning. 29(2-3):131-163.
0 runs0 likes0 downloads0 reach0 impact
weka.GaussianProcesses_NormalizedPolyKernel (2)
David J.C. Mackay (1998). Introduction to Gaussian Processes. Dept. of Physics, Cambridge University, UK.
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weka.NormalizedPolyKernel (2)
Weka implementation of NormalizedPolyKernel
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weka.GaussianProcesses_PrecomputedKernelMatrixKernel (2)
David J.C. Mackay (1998). Introduction to Gaussian Processes. Dept. of Physics, Cambridge University, UK.
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weka.PrecomputedKernelMatrixKernel (2)
Weka implementation of PrecomputedKernelMatrixKernel
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weka.GaussianProcesses_Puk (2)
David J.C. Mackay (1998). Introduction to Gaussian Processes. Dept. of Physics, Cambridge University, UK.
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weka.Puk (2)
B. Uestuen, W.J. Melssen, L.M.C. Buydens (2006). Facilitating the application of Support Vector Regression by using a universal Pearson VII function based kernel. Chemometrics and Intelligent…
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weka.KernelLogisticRegression_PolyKernel (2)
Weka implementation of KernelLogisticRegression
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weka.SimpleKMeans_EuclideanDistance (2)
D. Arthur, S. Vassilvitskii: k-means++: the advantages of carefull seeding. In: Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms, 1027-1035, 2007.
0 runs0 likes0 downloads0 reach0 impact
weka.EuclideanDistance (2)
Wikipedia. Euclidean distance. URL http://en.wikipedia.org/wiki/Euclidean_distance.
0 runs0 likes0 downloads0 reach0 impact
weka.ND_J48 (2)
Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems. In: PKDD, 84-95, 2005. Eibe Frank, Stefan Kramer: Ensembles of nested dichotomies for…
0 runs0 likes0 downloads0 reach0 impact
weka.Discretize (2)
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.GridSearch_PLSFilter_LinearRegression (1)
Weka implementation of GridSearch
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weka.MultiBoostAB_GaussianProcesses_PolyKernel (2)
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
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weka.RealAdaBoost_SMO_PolyKernel (1)
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.RotationForest_PrincipalComponents_HNB (2)
Juan J. Rodriguez, Ludmila I. Kuncheva, Carlos J. Alonso (2006). Rotation Forest: A new classifier ensemble method. IEEE Transactions on Pattern Analysis and Machine Intelligence. 28(10):1619-1630.…
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weka.RotationForest_PrincipalComponents_SPegasos (2)
Juan J. Rodriguez, Ludmila I. Kuncheva, Carlos J. Alonso (2006). Rotation Forest: A new classifier ensemble method. IEEE Transactions on Pattern Analysis and Machine Intelligence. 28(10):1619-1630.…
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weka.Prism (2)
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.Id3 (2)
R. Quinlan (1986). Induction of decision trees. Machine Learning. 1(1):81-106.
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weka.J48 (11)
Ross Quinlan (1993). C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo, CA.
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weka.J48 (12)
Ross Quinlan (1993). C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo, CA.
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weka.FilteredClassifier_MultiFilter_ClassAssigner_PLSClassifier_PLSFilter (1)
Weka implementation of FilteredClassifier
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weka.MultiFilter_ClassAssigner (1)
Weka implementation of MultiFilter
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weka.ClassAssigner (1)
Weka implementation of ClassAssigner
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weka.FilteredClassifier_MultiFilter_ClassAssigner_NaiveBayesMultinomial (1)
Weka implementation of FilteredClassifier
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weka.FilteredClassifier_MultiFilter_ReplaceMissingValues_NaiveBayes (1)
Weka implementation of FilteredClassifier
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weka.MultiFilter_ReplaceMissingValues (1)
Weka implementation of MultiFilter
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weka.ReplaceMissingValues (1)
Weka implementation of ReplaceMissingValues
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classif.rpart (3)
Learner classif.rpart from package(s) rpart.
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weka.AttributeSelection_Ranker_PrincipalComponents (1)
Weka implementation of AttributeSelection
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weka.Ranker (1)
Weka implementation of Ranker
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weka.PrincipalComponents (3)
Weka implementation of PrincipalComponents
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weka.InfoGainAttributeEval (1)
Weka implementation of InfoGainAttributeEval
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weka.AdditiveRegression_J48 (1)
J.H. Friedman (1999). Stochastic Gradient Boosting.
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GenericClustering (1)
For testing
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weka.NaiveBayes (3)
George H. John, Pat Langley: Estimating Continuous Distributions in Bayesian Classifiers. In: Eleventh Conference on Uncertainty in Artificial Intelligence, San Mateo, 338-345, 1995.
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weka.Logistic (4)
le Cessie, S., van Houwelingen, J.C. (1992). Ridge Estimators in Logistic Regression. Applied Statistics. 41(1):191-201.
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