Synopsis

MLC-BMaD - Multi-Label Classification using Boolean Matrix Decomposition. Transforms the labels using a Boolean matrix decomposition, the first resulting matrix are used as latent labels and a classifier is trained to predict them. The second matrix is used in a multiplication to decompress the predicted latent labels. For more information see: J"org Wicker, Bernhard Pfahringer, Stefan Kramer: Multi-Label Classification using Boolean Matrix Decomposition. In: Proceedings of the 27th Annual ACM Symposium on Applied Computing, 179-186, 2012.

BibTeX

@inproceedings{J"orgWicker2012,
   author = {J"org Wicker, Bernhard Pfahringer, Stefan Kramer},
   booktitle = {Proceedings of the 27th Annual ACM Symposium on Applied Computing},
   pages = {179-186},
   title = {Multi-Label Classification using Boolean Matrix Decomposition},
   year = {2012}
}

Options

  • -size <value>

    Size of the compressed matrix. Should be less than the number of labels and more than 1. (default: 20)

  • -threshold <value>

    Threshold for the matrix decompositon, what is considered frequent. Between 0 and 1. (default: 0.5)

  • -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).