3478 939 weka.AttributeSelectedClassifier_GainRatioAttributeEval_Ranker_MultilayerPerceptron 1 Weka_3.7.13_11461 Weka implementation of AttributeSelectedClassifier 2016-04-15T01:13:33 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 baselearner weka.attributeSelection.GainRatioAttributeEval 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 kernel weka.attributeSelection.Ranker 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.functions.MultilayerPerceptron 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 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 S 2118 780 weka.Ranker 3 Weka_3.7.13_11213 Weka implementation of Ranker 2015-12-04T23:53:19 English Weka_3.7.13 N option -1 Specify number of attributes to select P option Specify a starting set of attributes. Eg. 1,3,5-7. Any starting attributes specified are ignored during the ranking. T option -1.7976931348623157E308 Specify a theshold by which attributes may be discarded from the ranking. weka weka_3.7.13 E 2138 780 weka.GainRatioAttributeEval 1 Weka_3.7.13_11215 Weka implementation of GainRatioAttributeEval 2015-12-05T11:08:21 English Weka_3.7.13 M flag treat missing values as a seperate value. weka weka_3.7.13 Verified_Supervised_Classification weka weka_3.7.13 https://api.openml.org/data/download/1912415/weka.classifiers.meta.AttributeSelectedClassifier1624337606020690104.class class e33297e05015e5c2e3533a8e686b98eb