3956 1 weka.AttributeSelectedClassifier_END_ND_J48 1 Weka_3.7.13_11461 Weka implementation of AttributeSelectedClassifier 2016-06-01T16:27:32 English Weka_3.7.13 -do-not-check-capabilities flag If set, classifier capabilities are not checked before classifier is built (use with caution). -doNotMakeSplitPointActualValue flag Do not make split point actual value. A flag Laplace smoothing for predicted probabilities. B flag Use binary splits only. C option Set confidence threshold for pruning. (default 0.25) D flag Output debugging info. E option weka.attributeSelection.CfsSubsetEval -P 1 -E 1 Full class name of attribute evaluator, followed by its options. eg: "weka.attributeSelection.CfsSubsetEval -L" (default weka.attributeSelection.CfsSubsetEval) J flag Do not use MDL correction for info gain on numeric attributes. L flag Do not clean up after the tree has been built. M option Set minimum number of instances per leaf. (default 2) N option Set number of folds for reduced error pruning. One fold is used as pruning set. (default 3) O flag Do not collapse tree. P option The size of the thread pool, for example, the number of cores in the CPU. (default 1) Q option Seed for random data shuffling (default 1). R flag Use reduced error pruning. S option weka.attributeSelection.BestFirst -D 1 -N 5 Full class name of search method, followed by its options. eg: "weka.attributeSelection.BestFirst -D 1" (default weka.attributeSelection.BestFirst) U flag Use unpruned tree. W baselearner weka.classifiers.meta.END Full name of base classifier. (default: weka.classifiers.trees.J48) Z flag Precompute the full correlation matrix at the outset, rather than compute correlations lazily (as needed) during the search. Use this in conjuction with parallel processing in order to speed up a backward search. num-decimal-places option The number of decimal places for the output of numbers in the model (default 2). output-debug-info flag If set, classifier is run in debug mode and may output additional info to the console W 3957 1 weka.END_ND_J48 4 Weka_3.7.13_10342 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 multi-class problems. In: Twenty-first International Conference on Machine Learning, 2004. 2016-06-01T16:27:32 English Weka_3.7.13 -do-not-check-capabilities flag If set, classifier capabilities are not checked before classifier is built (use with caution). -doNotMakeSplitPointActualValue flag Do not make split point actual value. A flag Laplace smoothing for predicted probabilities. B flag Use binary splits only. C option Set confidence threshold for pruning. (default 0.25) I option 10 Number of iterations. (default 10) J flag Do not use MDL correction for info gain on numeric attributes. L flag Do not clean up after the tree has been built. M option Set minimum number of instances per leaf. (default 2) N option Set number of folds for reduced error pruning. One fold is used as pruning set. (default 3) O flag Do not collapse tree. Q option Seed for random data shuffling (default 1). R flag Use reduced error pruning. S option 1 Random number seed. (default 1) U flag Use unpruned tree. W baselearner weka.classifiers.meta.nestedDichotomies.ND Full name of base classifier. (default: weka.classifiers.meta.nestedDichotomies.ND) num-decimal-places option The number of decimal places for the output of numbers in the model (default 2). output-debug-info flag If set, classifier is run in debug mode and may output additional info to the console W 3958 1 weka.ND_J48 4 Weka_3.7.13_10342 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 multi-class problems. In: Twenty-first International Conference on Machine Learning, 2004. 2016-06-01T16:27:32 English Weka_3.7.13 -do-not-check-capabilities flag If set, classifier capabilities are not checked before classifier is built (use with caution). -doNotMakeSplitPointActualValue flag Do not make split point actual value. A flag Laplace smoothing for predicted probabilities. B flag Use binary splits only. C option Set confidence threshold for pruning. (default 0.25) J flag Do not use MDL correction for info gain on numeric attributes. L flag Do not clean up after the tree has been built. M option Set minimum number of instances per leaf. (default 2) N option Set number of folds for reduced error pruning. One fold is used as pruning set. (default 3) O flag Do not collapse tree. Q option Seed for random data shuffling (default 1). R flag Use reduced error pruning. S option 1 Random number seed. (default 1) U flag Use unpruned tree. W baselearner weka.classifiers.trees.J48 Full name of base classifier. (default: weka.classifiers.trees.J48) num-decimal-places option The number of decimal places for the output of numbers in the model (default 2). output-debug-info flag If set, classifier is run in debug mode and may output additional info to the console W 1720 1 weka.J48 33 Weka_3.7.13_11194 Ross Quinlan (1993). C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo, CA. 2015-10-30T12:49:47 English Weka_3.7.13 -do-not-check-capabilities flag If set, classifier capabilities are not checked before classifier is built (use with caution). -doNotMakeSplitPointActualValue flag Do not make split point actual value. A flag Laplace smoothing for predicted probabilities. B flag Use binary splits only. C option 0.25 Set confidence threshold for pruning. (default 0.25) J flag Do not use MDL correction for info gain on numeric attributes. L flag Do not clean up after the tree has been built. M option 2 Set minimum number of instances per leaf. (default 2) N option Set number of folds for reduced error pruning. One fold is used as pruning set. (default 3) O flag Do not collapse tree. Q option Seed for random data shuffling (default 1). R flag Use reduced error pruning. S flag Do not perform subtree raising. U flag Use unpruned tree. num-decimal-places option The number of decimal places for the output of numbers in the model (default 2). output-debug-info flag If set, classifier is run in debug mode and may output additional info to the console mythbusting mythbusting_1 study_15 study_20 study_34 study_73 Verified_Learning_Curve,Verified_Supervised_Classification weka weka_3.7.13 https://api.openml.org/data/download/1681027/weka.classifiers.trees.J481019998014146204943.class class 5bd92b1eff2acdcf46b59e1af99f0850 weka weka_3.7.13 Verified_Supervised_Classification weka weka_3.7.13 Verified_Supervised_Classification weka weka_3.7.13 https://api.openml.org/data/download/1987045/weka.classifiers.meta.AttributeSelectedClassifier5154092675438142575.class class 3810d67df89dd55d4f00d0243d84d107