599 2 weka.MultiBoostAB_MultilayerPerceptron 2 Weka_3.7.12-SNAPSHOT_8109 Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2). 2014-10-07T16:38:14 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). C option 3 Number of sub-committees. (Default 3) I option 10 Number of iterations. (default 10) P option 100 Percentage of weight mass to base training on. (default 100, reduce to around 90 speed up) Q flag Use resampling for boosting. S option 1 Random number seed. (default 1) W baselearner weka.classifiers.functions.MultilayerPerceptron Full name of base classifier. (default: weka.classifiers.trees.DecisionStump) output-debug-info flag If set, classifier is run in debug mode and may output additional info to the console W 416 2 weka.MultilayerPerceptron 2 Weka_3.7.12-SNAPSHOT_10169 Weka implementation of MultilayerPerceptron 2014-08-18T16:50:53 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). 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). output-debug-info flag If set, classifier is run in debug mode and may output additional info to the console Verified_Learning_Curve,Verified_Supervised_Classification Verified_Learning_Curve,Verified_Supervised_Classification https://api.openml.org/data/download/54579/weka.classifiers.meta.MultiBoostAB7544332309784210095.class class 78979b05808a5eec6b8776b175819763