weka.REPTree
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Uploaded 30-03-2017 by
Weka_3.8.1
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Weka implementation of REPTree
Parameters
| -do-not-check-capabilities | If set, classifier capabilities are not checked before classifier is built
(use with caution). | |
| I | Initial class value count (default 0) | default: 0.0 |
| L | Maximum tree depth (default -1, no maximum) | default: -1 |
| M | Set minimum number of instances per leaf (default 2). | default: 2 |
| N | Number of folds for reduced error pruning (default 3). | default: 3 |
| P | No pruning. | |
| R | Spread initial count over all class values (i.e. don't use 1 per value) | |
| S | Seed for random data shuffling (default 1). | default: 1 |
| V | Set minimum numeric class variance proportion
of train variance for split (default 1e-3). | default: 0.001 |
| batch-size | The desired batch size for batch prediction (default 100). | |
| num-decimal-places | The number of decimal places for the output of numbers in the model (default 2). | |
| output-debug-info | If set, classifier is run in debug mode and
may output additional info to the console | |
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