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weka.RandomForest (13)
Leo Breiman (2001). Random Forests. Machine Learning. 45(1):5-32.
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weka.SMO (1)
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,…
108 runs0 likes0 downloads0 reach0 impact
weka.OneR (1)
R.C. Holte (1993). Very simple classification rules perform well on most commonly used datasets. Machine Learning. 11:63-91.
0 runs0 likes0 downloads0 reach0 impact
weka.JRip (1)
William W. Cohen: Fast Effective Rule Induction. In: Twelfth International Conference on Machine Learning, 115-123, 1995.
0 runs0 likes0 downloads0 reach0 impact
weka.J48 (1)
Ross Quinlan (1993). C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo, CA.
0 runs0 likes0 downloads0 reach0 impact
weka.REPTree (1)
Weka implementation of REPTree
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weka.HoeffdingTree (1)
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.
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weka.LMT (1)
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…
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weka.NaiveBayes (1)
George H. John, Pat Langley: Estimating Continuous Distributions in Bayesian Classifiers. In: Eleventh Conference on Uncertainty in Artificial Intelligence, San Mateo, 338-345, 1995.
0 runs0 likes0 downloads0 reach0 impact
weka.IBk (1)
D. Aha, D. Kibler (1991). Instance-based learning algorithms. Machine Learning. 6:37-66.
0 runs0 likes0 downloads0 reach0 impact
weka.Logistic (1)
le Cessie, S., van Houwelingen, J.C. (1992). Ridge Estimators in Logistic Regression. Applied Statistics. 41(1):191-201.
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weka.MultilayerPerceptron (1)
Weka implementation of MultilayerPerceptron
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weka.RandomForest (1)
Leo Breiman (2001). Random Forests. Machine Learning. 45(1):5-32.
0 runs0 likes0 downloads0 reach0 impact
weka.Bagging (1)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
0 runs0 likes0 downloads0 reach0 impact
weka.AdaBoostM1 (1)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
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test2 (2)
test should be deleted
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test3 (1)
test should be deleted
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test4 (1)
test should be deleted
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weka.RandomForest (2)
Leo Breiman (2001). Random Forests. Machine Learning. 45(1):5-32.
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weka.RandomForest (3)
Leo Breiman (2001). Random Forests. Machine Learning. 45(1):5-32.
0 runs0 likes0 downloads0 reach0 impact
weka.RandomForest (4)
Leo Breiman (2001). Random Forests. Machine Learning. 45(1):5-32.
0 runs0 likes0 downloads0 reach0 impact
weka.RandomForest (6)
Leo Breiman (2001). Random Forests. Machine Learning. 45(1):5-32.
0 runs0 likes0 downloads0 reach0 impact
weka.RandomForest (5)
Leo Breiman (2001). Random Forests. Machine Learning. 45(1):5-32.
0 runs0 likes0 downloads0 reach0 impact
weka.RandomForest (7)
Leo Breiman (2001). Random Forests. Machine Learning. 45(1):5-32.
0 runs0 likes0 downloads0 reach0 impact
weka.RandomForest (8)
Leo Breiman (2001). Random Forests. Machine Learning. 45(1):5-32.
0 runs0 likes0 downloads0 reach0 impact
weka.RandomForest (9)
Leo Breiman (2001). Random Forests. Machine Learning. 45(1):5-32.
0 runs0 likes0 downloads0 reach0 impact
weka.RandomForest (10)
Leo Breiman (2001). Random Forests. Machine Learning. 45(1):5-32.
0 runs0 likes0 downloads0 reach0 impact
weka.RandomForest (11)
Leo Breiman (2001). Random Forests. Machine Learning. 45(1):5-32.
0 runs0 likes0 downloads0 reach0 impact
weka.RandomForest (12)
Leo Breiman (2001). Random Forests. Machine Learning. 45(1):5-32.
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weka.classifiers.meta.multisearch.RandomSearch (1)
Weka implementation.
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weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.lazy.IBk(weka.core.neighboursearch.LinearNNSearch(weka.core.EuclideanDistance))) (1)
Weka implementation.
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weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize) (1)
Weka implementation.
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weka.filters.unsupervised.attribute.ReplaceMissingValues (1)
Weka implementation.
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weka.filters.unsupervised.attribute.RemoveUseless (1)
Weka implementation.
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weka.filters.unsupervised.attribute.Normalize (1)
Weka implementation.
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weka.classifiers.lazy.IBk(weka.core.neighboursearch.LinearNNSearch(weka.core.EuclideanDistance)) (1)
D. Aha, D. Kibler (1991). Instance-based learning algorithms. Machine Learning. 6:37-66.
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weka.core.neighboursearch.LinearNNSearch(weka.core.EuclideanDistance) (1)
Weka implementation.
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weka.core.EuclideanDistance (1)
Wikipedia. Euclidean distance. URL http://en.wikipedia.org/wiki/Euclidean_distance.
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weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.RBFKernel,weka.classifiers.functions.Logistic)) (1)
Weka implementation.
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weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.RBFKernel,weka.classifiers.functions.Logistic) (1)
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.classifiers.functions.supportVector.RBFKernel (1)
Weka implementation.
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weka.classifiers.functions.Logistic (1)
le Cessie, S., van Houwelingen, J.C. (1992). Ridge Estimators in Logistic Regression. Applied Statistics. 41(1):191-201.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.functions.MultilayerPerceptron) (1)
Weka implementation.
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weka.classifiers.functions.MultilayerPerceptron (1)
Weka implementation.
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weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.functions.Logistic) (1)
Weka implementation.
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weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.trees.RandomForest) (1)
Weka implementation.
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weka.classifiers.trees.RandomForest (1)
Leo Breiman (2001). Random Forests. Machine Learning. 45(1):5-32.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic) (1)
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.classifiers.functions.supportVector.PolyKernel (1)
Weka implementation.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.rules.ZeroR_4f74de6e-97ee-45b6-9ae0-a50ef101ffe6 (1)
Weka implementation.
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weka.classifiers.rules.OneR_b1bcdd99-1bc6-413c-9eb4-9ecc0f83bb98 (1)
R.C. Holte (1993). Very simple classification rules perform well on most commonly used datasets. Machine Learning. 11:63-91.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.rules.JRip_1d9c8544-79b2-4fbe-b48d-e4b8be319120 (1)
William W. Cohen: Fast Effective Rule Induction. In: Twelfth International Conference on Machine Learning, 115-123, 1995.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)) (1)
Weka implementation.
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weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree) (1)
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
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weka.classifiers.meta.AdaBoostM1(weka.classifiers.trees.J48)_f549fed7-22bf-4e11-ae37-5da6ac11a0c8 (1)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.AdaBoostM1(weka.classifiers.bayes.NaiveBayes)_b69b2902-d59c-4dfa-8ad5-8ddf854f0ffc (1)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.Bagging(weka.classifiers.trees.REPTree)_0db7fb1c-083a-49b2-95d6-1ba7ac0867f8 (1)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.lazy.IBk(weka.core.neighboursearch.LinearNNSearch(weka.core.EuclideanDistance))_7d08b5fb-2416-4fc7-a2dc-f7f5c546d1e3 (1)
D. Aha, D. Kibler (1991). Instance-based learning algorithms. Machine Learning. 6:37-66.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.PolyKernel,weka.classifiers.functions.Logistic)_1452c951-cd46-46b6-bcfc-8ce4460f2838 (1)
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.classifiers.functions.Logistic_0c301415-4acb-4785-b522-6def35292cfc (1)
le Cessie, S., van Houwelingen, J.C. (1992). Ridge Estimators in Logistic Regression. Applied Statistics. 41(1):191-201.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.FilteredClassifier(weka.filters.unsupervised.attribute.Normalize,weka.classifiers.trees.J48)_e906bc88-4d66-4100-a6e0-91ea53ad017d (1)
Weka implementation.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.FilteredClassifier(weka.filters.unsupervised.attribute.RemoveUseless,weka.classifiers.trees.J48)_1eaa174c-e72e-4e3a-9a95-61a7d9606352 (1)
Weka implementation.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.Bagging(weka.classifiers.trees.J48)_ba74226d-a6e7-4ddc-bf58-f4d6fe6b296b (1)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.Bagging(weka.classifiers.bayes.NaiveBayes)_02cb96a7-556f-449e-8198-cf31011bc5d4 (1)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.functions.MultilayerPerceptron_cd2a8fe4-c941-42ec-93f8-276fe4f105e8 (1)
Weka implementation.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.trees.RandomForest_a36139d7-dedc-4c54-92d3-d46cb8cac452 (1)
Leo Breiman (2001). Random Forests. Machine Learning. 45(1):5-32.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.Bagging(weka.classifiers.trees.REPTree)_1c75e127-28db-42f7-90d4-bd36e117405d (1)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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weka.classifiers.trees.DecisionStump (1)
Weka implementation.
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weka.classifiers.meta.AdaBoostM1(weka.classifiers.trees.DecisionStump)_61f77b0b-4977-4941-b881-6564c0e16714 (1)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
0 runs0 likes0 downloads0 reach0 impact
weka.filters.supervised.attribute.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.classifiers.meta.FilteredClassifier(weka.filters.supervised.attribute.Discretize,weka.classifiers.trees.J48)_b7ea229b-31ec-466b-ac04-08622ca73b44 (1)
Weka implementation.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.AdaBoostM1(weka.classifiers.trees.REPTree)_b3961e08-b330-470b-b569-d9516f711ae6 (1)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.trees.J48_1f0d9772-0e7b-4125-b9d4-8e787ec80bd4 (1)
Ross Quinlan (1993). C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo, CA.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.trees.REPTree_7ee8d8ef-86a9-4d16-915c-5e010f43724e (1)
Weka implementation.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.trees.HoeffdingTree_019e138d-46f9-493b-8ca3-48b081e9a0a8 (1)
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.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.trees.LMT_70d01d36-8c2d-4099-a489-5cc9ad514578 (1)
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…
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.bayes.NaiveBayes_893936dd-49b5-4083-b8d9-92b1367c047c (1)
George H. John, Pat Langley: Estimating Continuous Distributions in Bayesian Classifiers. In: Eleventh Conference on Uncertainty in Artificial Intelligence, San Mateo, 338-345, 1995.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.Bagging(weka.classifiers.trees.REPTree)_a19f0f20-c46a-4937-97df-733732ecf485 (1)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.Bagging(weka.classifiers.trees.REPTree) (1)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.AdaBoostM1(weka.classifiers.meta.Bagging(weka.classifiers.trees.REPTree))_79dce145-e0c3-47da-89ec-7ed80cb930b8 (1)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.Bagging(weka.classifiers.meta.AdaBoostM1(weka.classifiers.trees.REPTree)) (1)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.AdaBoostM1(weka.classifiers.meta.Bagging(weka.classifiers.meta.AdaBoostM1(weka.classifiers.trees.REPTree)))_e3dcdda9-5ad9-425c-8dd6-d62e2004064e (1)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.Bagging(weka.classifiers.meta.Bagging(weka.classifiers.meta.AdaBoostM1(weka.classifiers.trees.REPTree)))_699091da-ea14-4d9a-8a4b-e1640dc113f7 (1)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.Bagging(weka.classifiers.meta.AdaBoostM1(weka.classifiers.meta.AdaBoostM1(weka.classifiers.trees.REPTree)))_a5cefba7-e377-45a9-a5e8-7d79a99fdb54 (1)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.Bagging(weka.classifiers.meta.AdaBoostM1(weka.classifiers.trees.REPTree))_d8d6d9f8-fbd7-462b-b65a-e5c5cf2e3a2f (1)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
0 runs0 likes0 downloads0 reach0 impact
weka.core.neighboursearch.KDTree(weka.core.neighboursearch.kdtrees.SlidingMidPointOfWidestSide,weka.core.EuclideanDistance) (1)
Jerome H. Friedman, Jon Luis Bentley, Raphael Ari Finkel (1977). An Algorithm for Finding Best Matches in Logarithmic Expected Time. ACM Transactions on Mathematics Software. 3(3):209-226. Andrew…
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weka.core.neighboursearch.kdtrees.SlidingMidPointOfWidestSide (1)
David M. Mount (2006). ANN Programming Manual. College Park, MD, USA.
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weka.classifiers.lazy.IBk(weka.core.neighboursearch.KDTree(weka.core.neighboursearch.kdtrees.SlidingMidPointOfWidestSide,weka.core.EuclideanDistance))_52c246bf-dac7-4969-8a08-50d8b0db6197 (1)
D. Aha, D. Kibler (1991). Instance-based learning algorithms. Machine Learning. 6:37-66.
0 runs0 likes0 downloads0 reach0 impact
weka.core.neighboursearch.CoverTree(weka.core.EuclideanDistance) (1)
Alina Beygelzimer, Sham Kakade, John Langford: Cover trees for nearest neighbor. In: ICML'06: Proceedings of the 23rd international conference on Machine learning, New York, NY, USA, 97-104, 2006.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.lazy.IBk(weka.core.neighboursearch.CoverTree(weka.core.EuclideanDistance))_9a3e6546-fbcc-400d-aa60-918ca76bca78 (1)
D. Aha, D. Kibler (1991). Instance-based learning algorithms. Machine Learning. 6:37-66.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.FilteredClassifier(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.classifiers.trees.J48)_d18b7835-94e4-41d7-bd1f-fff24413225a (1)
Weka implementation.
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weka.filters.unsupervised.attribute.StringToWordVector(weka.core.tokenizers.WordTokenizer) (1)
Weka implementation.
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weka.core.tokenizers.WordTokenizer (1)
Weka implementation.
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weka.classifiers.meta.FilteredClassifier(weka.filters.unsupervised.attribute.StringToWordVector(weka.core.tokenizers.WordTokenizer),weka.classifiers.trees.J48)_819584a4-6667-4032-8342-e24086e3ef64 (1)
Weka implementation.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.AdaBoostM1(weka.classifiers.trees.REPTree)_7c6b2c99-7a16-4084-92e9-af12dacd3e68 (1)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.AdaBoostM1(weka.classifiers.trees.REPTree) (1)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.AdaBoostM1(weka.classifiers.meta.AdaBoostM1(weka.classifiers.trees.REPTree))_55ada4e1-8b5d-47e7-b766-2320e0d4c4b1 (1)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.AdaBoostM1(weka.classifiers.meta.Bagging(weka.classifiers.trees.REPTree)) (1)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.AdaBoostM1(weka.classifiers.meta.AdaBoostM1(weka.classifiers.meta.Bagging(weka.classifiers.trees.REPTree)))_8870456e-bb29-46ac-a779-ce7283c2eebe (1)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.AdaBoostM1(weka.classifiers.meta.AdaBoostM1(weka.classifiers.trees.REPTree)) (1)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
0 runs0 likes0 downloads0 reach0 impact