Synopsis#

CC in a trellis structure (rather than a cascaded chain). You set the width and type/connectivity of the trellis, and optionally change the payoff function which guides the placement of nodes (labels) within the trellis.

BibTeX#

@article{JesseRead2015,
   author = {Jesse Read, Luca Martino, David Luengo, Pablo Olmos},
   journal = {Pattern Recognition},
   title = {Scalable multi-output label prediction: From classifier chains to classifier trellises},
   year = {2015},
   URL = {http://www.sciencedirect.com/science/article/pii/S0031320315000084}
}

Options#

  • -H <value>

    Determines the width of the trellis (use 0 for chain; use -1 for a square trellis, i.e., width of sqrt(number of labels)).

  • -L <value>

    Determines the neighbourhood density (the number of neighbours for each node in the trellis). Default = 1, BR = 0.

  • -X <value>

    The dependency heuristic to use in rearranging the trellis (applicable if chain iterations > 0), default: Ibf (Mutual Information, fast binary version for multi-label data)

  • -Is <value>

    The number of iterations to search the chain space at train time. default: 0

  • -Iy <value>

    The number of iterations to search the output space at test time. default: 10

  • -P <value>

    Sets the payoff function. Any of those listed in regular evaluation output will do (e.g., 'Exact match'). default: Exact match

  • -S <value>

    The seed value for randomizing the data. (default: 0)

  • -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).