4016 1 weka.FilteredClassifier_MultiSearch_SMO_RBFKernel 1 Weka_3.7.13_11958 Weka implementation of FilteredClassifier 2016-06-13T14:36:53 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 binary attributes for discretized attributes. E flag Use better encoding of split point for MDL. F option weka.filters.supervised.attribute.Discretize -R first-last -precision 6 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.meta.MultiSearch Full name of base classifier. (default: weka.classifiers.trees.J48) Y flag Use bin numbers rather than ranges for discretized attributes. 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 precision option Precision for bin boundary labels. (default = 6 decimal places). W 4017 1 weka.MultiSearch_SMO_RBFKernel 2 Weka_3.7.13_4521 Weka implementation of MultiSearch 2016-06-13T14:36:53 English Weka_3.7.13 -do-not-check-capabilities flag If set, classifier capabilities are not checked before classifier is built (use with caution). C flag Do not try to eliminate colinear attributes. E option CC Determines the parameter used for evaluation: CC = Correlation coefficient MCC = Matthews correlation coefficient RMSE = Root mean squared error RRSE = Root relative squared error MAE = Mean absolute error RAE = Root absolute error COMB = Combined = (1-abs(CC)) + RRSE + RAE ACC = Accuracy KAP = Kappa PREC = Precision (per class) WPREC = Weighted precision REC = Recall (per class) WREC = Weighted recall AUC = Area under ROC (per class) WAUC = Weighted area under ROC PRC = Area under PRC (per class) WPRC = Weighted area under PRC FM = F-Measure (per class) WFM = Weighted F-Measure TPR = True positive rate (per class) TNR = True negative rate (per class) FPR = False positive rate (per class) FNR = False negative rate (per class) (default: CC) R option Set ridge parameter (default 1.0e-8). S option 1 Random number seed. (default 1) W baselearner weka.classifiers.functions.SMO Full name of base classifier. (default: weka.classifiers.functions.LinearRegression) additional-stats flag Output additional statistics. algorithm option weka.classifiers.meta.multisearch.DefaultSearch -sample-size 100.0 -initial-folds 2 -subsequent-folds 10 -initial-test-set . -subsequent-test-set . -num-slots 1 -num-slots 1 A search algorithm. class-label option 1 The class label index to retrieve the metric for (if applicable). log-file option /home/rijnjnvan/apps/weka-3-7-13 The log file to log the messages to. (default: none) minimal flag Conserve memory, don't keep dataset header and means/stdevs. Model cannot be printed out if this option is enabled. (default: keep data) 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 search array A property search setup. W 4018 1 weka.SMO_RBFKernel 7 Weka_3.7.13_10141 J. Platt: Fast Training of Support Vector Machines using Sequential Minimal Optimization. In B. Schoelkopf and C. Burges and A. Smola, editors, Advances in Kernel Methods - Support Vector Learning, 1998. S.S. Keerthi, S.K. Shevade, C. Bhattacharyya, K.R.K. Murthy (2001). Improvements to Platt's SMO Algorithm for SVM Classifier Design. Neural Computation. 13(3):637-649. Trevor Hastie, Robert Tibshirani: Classification by Pairwise Coupling. In: Advances in Neural Information Processing Systems, 1998. 2016-06-13T14:36:53 English Weka_3.7.13 -do-not-check-capabilities flag If set, classifier capabilities are not checked before classifier is built (use with caution). C option 1.0 The complexity constant C. (default 1) E option The Exponent to use. (default: 1.0) K kernel weka.classifiers.functions.supportVector.RBFKernel The Kernel to use. (default: weka.classifiers.functions.supportVector.PolyKernel) L option 0.001 The tolerance parameter. (default 1.0e-3) M flag Fit logistic models to SVM outputs. N option 0 Whether to 0=normalize/1=standardize/2=neither. (default 0=normalize) P option 1.0E-12 The epsilon for round-off error. (default 1.0e-12) V option -1 The number of folds for the internal cross-validation. (default -1, use training data) W option 1 The random number seed. (default 1) no-checks flag Turns off all checks - use with caution! Turning them off assumes that data is purely numeric, doesn't contain any missing values, and has a nominal class. Turning them off also means that no header information will be stored if the machine is linear. Finally, it also assumes that no instance has a weight equal to 0. (default: checks on) 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 K 2231 2 weka.RBFKernel 4 Weka_3.7.13_11896 Weka implementation of RBFKernel 2015-12-22T15:22:05 English Weka_3.7.13 C option 250007 The size of the cache (a prime number), 0 for full cache and -1 to turn it off. (default: 250007) G option 0.01 The Gamma parameter. (default: 0.01) no-checks flag Turns off all checks - use with caution! (default: checks on) output-debug-info flag Enables debugging output (if available) to be printed. (default: off) weka weka_3.7.13 weka weka_3.7.13 weka weka_3.7.13 study_14 Verified_Supervised_Classification weka weka_3.7.13 https://api.openml.org/data/download/2035719/weka.classifiers.meta.FilteredClassifier3824247799390133201.class class af48820ceb4953af57f4a2cbbbc4d9be