weka.classifiers.meta.Bagging(weka.classifiers.meta.AdaBoostM1(weka.classifiers.meta.AdaBoostM1(weka.classifiers.trees.REPTree)))_a34581f7-c337-4703-834d-2b9e9e69e2fa
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Uploaded 18-10-2024 by
Jan van Rijn
Weka_3.9.6
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Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
Parameters
| -do-not-check-capabilities | If set, classifier capabilities are not checked before classifier is built
(use with caution). | default: ["false"] |
| I | Number of iterations.
(current value 10) | default: ["10"] |
| O | Calculate the out of bag error. | default: ["false"] |
| P | Size of each bag, as a percentage of the
training set size. (default 100) | default: ["100"] |
| S | Random number seed.
(default 1) | default: ["1"] |
| W | Full name of base classifier.
(default: weka.classifiers.trees.REPTree) | default: ["weka.classifiers.meta.AdaBoostM1"] |
| batch-size | The desired batch size for batch prediction (default 100). | default: [] |
| num-decimal-places | The number of decimal places for the output of numbers in the model (default 2). | default: [] |
| num-slots | Number of execution slots.
(default 1 - i.e. no parallelism)
(use 0 to auto-detect number of cores) | default: ["1"] |
| output-debug-info | If set, classifier is run in debug mode and
may output additional info to the console | default: ["false"] |
| output-out-of-bag-complexity-statistics | Whether to output complexity-based statistics when out-of-bag evaluation is performed. | default: ["false"] |
| print | Print the individual classifiers in the output | default: ["false"] |
| represent-copies-using-weights | Represent copies of instances using weights rather than explicitly. | default: ["false"] |
| store-out-of-bag-predictions | Whether to store out of bag predictions in internal evaluation object. | default: ["false"] |
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