Synopsis#

A Deep Back-Propagation Neural Network. For more information see: Geoffrey Hinton, Ruslan Salakhutdinov (2006). Reducing the Dimensionality of Data with Neural Networks. Science. 313(5786):504-507.

BibTeX#

@article{Hinton2006,
   author = {Geoffrey Hinton and Ruslan Salakhutdinov},
   journal = {Science},
   number = {5786},
   pages = {504-507},
   title = {Reducing the Dimensionality of Data with Neural Networks},
   volume = {313},
   year = {2006}
}

Options#

• -N <value>

  Sets the number of RBMs default: 2

• -H <value>

  Sets the number of hidden units default: 10

• -E <value>

  Sets the maximum number of epochs default: 1000 (auto-cut-out)

• -r <value>

  Sets the learning rate (tyically somewhere between 'very small' and 0.1) default: 0.1

• -m <value>

  Sets the momentum (typically somewhere between 0.1 and 0.9) default: 0.1

• -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).