Synopsis#

A Conditional Dependency Trellis. Like CDN, but with a trellis structure (like CT) rather than a fully connected network.For more information see: Yuhong Guoand, Suicheng Gu (2011). Multi-Label Classification Using Conditional Dependency Networks.

Jesse Read, Luca Martino, David Luengo, Pablo Olmos (2015). Scalable multi-output label prediction: From classifier chains to classifier trellises. Pattern Recognition.. URL http://www.sciencedirect.com/science/article/pii/S0031320315000084.

BibTeX#

@article{Guoand2011,
   author = {Yuhong Guoand and Suicheng Gu},
   booktitle = {IJCAI '11},
   title = {Multi-Label Classification Using Conditional Dependency Networks},
   year = {2011}
}

@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).

• -X <value>

  The dependency heuristic to use in rearranging the trellis (None by default).

• -I <value>

  The total number of iterations. default: 1000

• -Ic <value>

  The number of collection iterations. default: 100

• -S <value>

  The seed value for randomization.

• -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).