4295 1 weka.Bagging_MultilayerPerceptron 3 Weka_3.7.13_11465 Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140. 2016-08-16T14:49:46 English Weka_3.7.13 -do-not-check-capabilities flag If set, classifier capabilities are not checked before classifier is built (use with caution). -represent-copies-using-weights flag Represent copies of instances using weights rather than explicitly. I option 10 Number of iterations. (default 10) L option Maximum tree depth (default -1, no maximum) M option Set minimum number of instances per leaf (default 2). N option Number of folds for reduced error pruning (default 3). O flag Calculate the out of bag error. P option 100 Size of each bag, as a percentage of the training set size. (default 100) R flag Spread initial count over all class values (i.e. don't use 1 per value) S option 1 Random number seed. (default 1) V option Set minimum numeric class variance proportion of train variance for split (default 1e-3). W baselearner weka.classifiers.functions.MultilayerPerceptron Full name of base classifier. (default: weka.classifiers.trees.REPTree) num-decimal-places option The number of decimal places for the output of numbers in the model (default 2). num-slots option 1 Number of execution slots. (default 1 - i.e. no parallelism) (use 0 to auto-detect number of cores) output-debug-info flag If set, classifier is run in debug mode and may output additional info to the console W 1820 767 weka.MultilayerPerceptron 4 Weka_3.7.13_10169 Weka implementation of MultilayerPerceptron 2015-11-25T19:00:43 English Weka_3.7.13 -do-not-check-capabilities flag If set, classifier capabilities are not checked before classifier is built (use with caution). A flag Autocreation of the network connections will NOT be done. (This will be ignored if -G is NOT set) B flag A NominalToBinary filter will NOT automatically be used. (Set this to not use a NominalToBinary filter). C flag Normalizing a numeric class will NOT be done. (Set this to not normalize the class if it's numeric). D flag Learning rate decay will occur. (Set this to cause the learning rate to decay). E option 20 The consequetive number of errors allowed for validation testing before the netwrok terminates. (Value should be > 0, Default = 20). G flag GUI will be opened. (Use this to bring up a GUI). H option a The hidden layers to be created for the network. (Value should be a list of comma separated Natural numbers or the letters 'a' = (attribs + classes) / 2, 'i' = attribs, 'o' = classes, 't' = attribs .+ classes) for wildcard values, Default = a). I flag Normalizing the attributes will NOT be done. (Set this to not normalize the attributes). L option 0.3 Learning Rate for the backpropagation algorithm. (Value should be between 0 - 1, Default = 0.3). M option 0.2 Momentum Rate for the backpropagation algorithm. (Value should be between 0 - 1, Default = 0.2). N option 500 Number of epochs to train through. (Default = 500). R flag Reseting the network will NOT be allowed. (Set this to not allow the network to reset). S option 0 The value used to seed the random number generator (Value should be >= 0 and and a long, Default = 0). V option 0 Percentage size of validation set to use to terminate training (if this is non zero it can pre-empt num of epochs. (Value should be between 0 - 100, Default = 0). 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 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/1682546/weka.classifiers.functions.MultilayerPerceptron4217900601518466169.class class 9f3d66acadd8b011519791d8c12b4f35 Verified_Learning_Curve,Verified_Supervised_Classification weka weka_3.7.13 https://api.openml.org/data/download/4538134/weka.classifiers.meta.Bagging7042671548180458317.class class 656bf8da26e0af26022f2826e81a341f