Synopsis#

HOMER tree algorithm. For more information see: Tsoumakas, Grigorios, Katakis, Ioannis, Vlahavas, Ioannis: Effective and efficient multilabel classification in domains with large number of labels. In: Proc. ECML/PKDD 2008 Workshop on Mining Multidimensional Data (MMD’08), 53--59, 2008.

BibTeX#

@inproceedings{Tsoumakas2008,
   author = {Tsoumakas, Grigorios and Katakis, Ioannis and Vlahavas, Ioannis},
   booktitle = {Proc. ECML/PKDD 2008 Workshop on Mining Multidimensional Data (MMD’08)},
   organization = {sn},
   pages = {53--59},
   title = {Effective and efficient multilabel classification in domains with large number of labels},
   volume = {21},
   year = {2008}
}

Options#

  • -k K

    The number of partitions per level.

  • -S seed

    The seed to set.

  • -ls class

    The label splitter class to use.

  • -t threshold

    The threshold for the multi-label classifier distribution

  • -W <classifier name>

    Full name of base classifier. (default: meka.classifiers.multilabel.BR)

  • -output-debug-info

    If set, classifier is run in debug mode and may output additional info to the console

  • -do-not-check-capabilities

    If set, classifier capabilities are not checked before classifier is built (use with caution).

  • -num-decimal-places

    The number of decimal places for the output of numbers in the model (default 2).

  • -batch-size

    The desired batch size for batch prediction (default 100).

Options specific to classifier meka.classifiers.multilabel.BR:

  • -W <classifier name>

    Full name of base classifier. (default: weka.classifiers.trees.J48)

  • -output-debug-info

    If set, classifier is run in debug mode and may output additional info to the console

  • -do-not-check-capabilities

    If set, classifier capabilities are not checked before classifier is built (use with caution).

  • -num-decimal-places

    The number of decimal places for the output of numbers in the model (default 2).

  • -batch-size

    The desired batch size for batch prediction (default 100).

Options specific to classifier weka.classifiers.trees.J48:

  • -U

    Use unpruned tree.

  • -O

    Do not collapse tree.

  • -C <pruning confidence>

    Set confidence threshold for pruning. (default 0.25)

  • -M <minimum number of instances>

    Set minimum number of instances per leaf. (default 2)

  • -R

    Use reduced error pruning.

  • -N <number of folds>

    Set number of folds for reduced error pruning. One fold is used as pruning set. (default 3)

  • -B

    Use binary splits only.

  • -S

    Do not perform subtree raising.

  • -L

    Do not clean up after the tree has been built.

  • -A

    Laplace smoothing for predicted probabilities.

  • -J

    Do not use MDL correction for info gain on numeric attributes.

  • -Q <seed>

    Seed for random data shuffling (default 1).

  • -doNotMakeSplitPointActualValue

    Do not make split point actual value.

  • -output-debug-info

    If set, classifier is run in debug mode and may output additional info to the console

  • -do-not-check-capabilities

    If set, classifier capabilities are not checked before classifier is built (use with caution).

  • -num-decimal-places

    The number of decimal places for the output of numbers in the model (default 2).

  • -batch-size

    The desired batch size for batch prediction (default 100).