711 1 weka.FilteredClassifier_Discretize_J48 3 Weka_3.7.12-SNAPSHOT_11142 Weka implementation of FilteredClassifier 2014-11-15T12:57:53 English Weka_3.7.12-SNAPSHOT -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 binary attributes for discretized attributes. E flag Use better encoding of split point for MDL. F kernel weka.filters.supervised.attribute.Discretize Full class name of filter to use, followed by filter options. eg: "weka.filters.unsupervised.attribute.Remove -V -R 1,2" J flag Do not use MDL correction for info gain on numeric attributes. K flag Use Kononenko's MDL criterion. 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 flag Do not perform subtree raising. U flag Use unpruned tree. V flag Invert matching sense of column indexes. W baselearner weka.classifiers.trees.J48 Full name of base classifier. (default: weka.classifiers.trees.J48) Y flag Use bin numbers rather than ranges for discretized attributes. output-debug-info flag If set, classifier is run in debug mode and may output additional info to the console precision option Precision for bin boundary labels. (default = 6 decimal places). F 588 2 weka.Discretize 2 Weka_3.7.12-SNAPSHOT_10231 Usama M. Fayyad, Keki B. Irani: Multi-interval discretization of continuousvalued attributes for classification learning. In: Thirteenth International Joint Conference on Articial Intelligence, 1022-1027, 1993. Igor Kononenko: On Biases in Estimating Multi-Valued Attributes. In: 14th International Joint Conference on Articial Intelligence, 1034-1040, 1995. 2014-10-07T15:41:16 English Weka_3.7.12-SNAPSHOT D flag Output binary attributes for discretized attributes. E flag Use better encoding of split point for MDL. K flag Use Kononenko's MDL criterion. R option first-last Specifies list of columns to Discretize. First and last are valid indexes. (default none) V flag Invert matching sense of column indexes. Y flag Use bin numbers rather than ranges for discretized attributes. precision option 6 Precision for bin boundary labels. (default = 6 decimal places). W 675 2 weka.J48 13 Weka_3.7.12-SNAPSHOT_11194 Ross Quinlan (1993). C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo, CA. 2014-10-30T11:53:26 English Weka_3.7.12-SNAPSHOT -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. output-debug-info flag If set, classifier is run in debug mode and may output additional info to the console study_2 study_37 study_73 Verified_Learning_Curve,Verified_Supervised_Classification https://api.openml.org/data/download/116690/weka.classifiers.trees.J483562716070411093887.class class 6d8bbe1e017bcbd4d08fc5789ea9385e curves Verified_Learning_Curve weka weka_3.7.12-SNAPSHOT https://api.openml.org/data/download/158699/weka.classifiers.meta.FilteredClassifier8235740895629556169.class class ee67ef8dace0cae2835a61defe36d1aa