252 2 weka.RotationForest_PrincipalComponents_ZeroR 1 Weka_3.7.10_8108 Juan J. Rodriguez, Ludmila I. Kuncheva, Carlos J. Alonso (2006). Rotation Forest: A new classifier ensemble method. IEEE Transactions on Pattern Analysis and Machine Intelligence. 28(10):1619-1630. URL http://doi.ieeecomputersociety.org/10.1109/TPAMI.2006.211. 2014-06-03T21:32:34 English Weka_3.7.10 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 If set, classifier is run in debug mode and may output additional info to the console F kernel weka.filters.unsupervised.attribute.PrincipalComponents Full class name of filter to use, followed by filter options. eg: "weka.filters.unsupervised.attribute.PrincipalComponents-R 1.0" G option 3 Minimum size of a group of attributes: if numberOfGroups is true, the minimum number of groups. (default: 3) H option 3 Maximum size of a group of attributes: if numberOfGroups is true, the maximum number of groups. (default: 3) I option 10 Number of iterations. (default 10) 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 flag Whether minGroup (-G) and maxGroup (-H) refer to the number of groups or their size. (default: false) O flag Do not collapse tree. P option 50 Percentage of instances to be removed. (default: 50) Q option Seed for random data shuffling (default 1). R flag Use reduced error pruning. S option 1 Random number seed. (default 1) U flag Use unpruned tree. W baselearner weka.classifiers.rules.ZeroR Full name of base classifier. (default: weka.classifiers.trees.J48) num-slots option 1 Number of execution slots. (default 1 - i.e. no parallelism) W 56 1 weka.ZeroR 1 Weka_3.7.10_8034 Weka implementation of ZeroR 2014-04-04T14:38:33 English Weka_3.7.10 D flag If set, classifier is run in debug mode and may output additional info to the console study_7 Verified_Learning_Curve,Verified_Supervised_Classification,Verified_Supervised_Data_Stream_Classification F 244 2 weka.PrincipalComponents 1 Weka_3.7.10_8034 Weka implementation of PrincipalComponents 2014-06-03T21:18:32 English Weka_3.7.10 A option 5 Maximum number of attributes to include in transformed attribute names. (-1 = include all, default: 5) C flag Center (rather than standardize) the data and compute PCA using the covariance (rather than the correlation) matrix. M option -1 Maximum number of PC attributes to retain. (-1 = include all, default: -1) R option 0.95 Retain enough PC attributes to account for this proportion of variance in the original data. (default: 0.95) Verified_Supervised_Classification https://api.openml.org/data/download/30703/weka.classifiers.meta.RotationForest2069562666615166061.class class c26fb92d6b30c61b4d3986535e42dd25