-do-not-check-capabilities | If set, classifier capabilities are not checked before classifier is built
(use with caution). | |
A | The nearest neighbour search algorithm to use (default: weka.core.neighboursearch.LinearNNSearch). | |
D | The distribution to use for calculating the random matrix.
Sparse1 is:
sqrt(3)*{-1 with prob(1/6), 0 with prob(2/3), +1 with prob(1/6)}
Sparse2 is:
{-1 with prob(1/2), +1 with prob(1/2)} | |
E | Minimise mean squared error rather than mean absolute
error when using -X option with numeric prediction. | |
F | Full class name of filter to use, followed
by filter options.
eg: "weka.filters.unsupervised.attribute.Remove -V -R 1,2" | default: weka.filters.unsupervised.attribute.RandomProjection -N 10 -R 42 -D Sparse1 |
I | Weight neighbours by the inverse of their distance
(use when k > 1) | |
K | Number of nearest neighbours (k) used in classification.
(Default = 1) | |
M | Replace missing values using the ReplaceMissingValues filter | |
N | The number of dimensions (attributes) the data should be reduced to
(default 10; exclusive of the class attribute, if it is set). | |
P | The percentage of dimensions (attributes) the data should
be reduced to (exclusive of the class attribute, if it is set). The -N
option is ignored if this option is present and is greater
than zero. | |
R | The random seed for the random number generator used for
calculating the random matrix (default 42). | |
S | Random number seed.
(default 1) | default: 1 |
W | Full name of base classifier.
(default: weka.classifiers.lazy.IBk) | default: weka.classifiers.meta.Stacking |
X | Select the number of nearest neighbours between 1
and the k value specified using hold-one-out evaluation
on the training data (use when k > 1) | |
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 | |