Issue | #Downvotes for this reason | By |
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W | weka.MultilayerPerceptron(8) | Full name of base classifier. (default: weka.classifiers.trees.RandomTree) |
-do-not-check-capabilities | If set, classifier capabilities are not checked before classifier is built (use with caution). | |
B | Break ties randomly when several attributes look equally good. | |
I | Number of iterations. (current value 10) | default: 10 |
K | Number of attributes to randomly investigate. (default 0) (<1 = int(log_2(#predictors)+1)). | |
M | Set minimum number of instances per leaf. (default 1) | |
N | Number of folds for backfitting (default 0, no backfitting). | |
S | Random number seed. (default 1) | default: 1 |
U | Allow unclassified instances. | |
V | Set minimum numeric class variance proportion of train variance for split (default 1e-3). | |
W | Full name of base classifier. (default: weka.classifiers.trees.RandomTree) | default: weka.classifiers.functions.MultilayerPerceptron |
batch-size | The desired batch size for batch prediction (default 100). | |
depth | The maximum depth of the tree, 0 for unlimited. (default 0) | |
num-decimal-places | The number of decimal places for the output of numbers in the model (default 2). | |
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 |