FCNN4R: Fast Compressed Neural Networks for R

Provides an interface to kernel routines from the FCNN C++ library. FCNN is based on a completely new Artificial Neural Network representation that offers unmatched efficiency, modularity, and extensibility. FCNN4R provides standard teaching (backpropagation, Rprop, simulated annealing, stochastic gradient) and pruning algorithms (minimum magnitude, Optimal Brain Surgeon), but it is first and foremost an efficient computational engine. Users can easily implement their algorithms by taking advantage of fast gradient computing routines, as well as network reconstruction functionality (removing weights and redundant neurons, reordering inputs, merging networks). Networks can be exported to C functions in order to integrate them into virtually any software solution.

AuthorGrzegorz Klima <gklima@users.sourceforge.net>
Date of publication2016-03-09 00:57:57
MaintainerGrzegorz Klima <gklima@users.sourceforge.net>
LicenseGPL (>= 2)
Version0.6.2

View on CRAN

Man pages

FCNN4R-package: Fast Compressed Neural Networks for R

is.mlp_net: Is it an object of 'mlp_net' class?

mlp_actvfunc2str: Return character string representing activation function

mlp_check_inout: Check validity of inputs and outputs

mlp_check_w: Check validity of weight index

mlp_eval: Evaluation

mlp_export_C: Export multilayer perceptron network to a C function

mlp_net: Create objects of 'mlp_net' class

mlp_net-absolute-weight-indices: Retrieving absolute weight index

mlp_net-accessing-individual-weights: Setting and retrieving status (on/off) and value of...

mlp_net-class: An S4 class representing Multilayer Perception Network.

mlp_net-combining-two-networks: Combining two networks into one

mlp_net-display: Displaying networks (objects of 'mlp_net' class)

mlp_net-export-import: Export and import multilayer perceptron network to/from a...

mlp_net-general-information: General information about network

mlp_net-manipulating-network-inputs: Manipulating network inputs

mlp_net-MSE-gradients: Computing mean squared error, its gradient, and output...

mlp_net-names: Get and set network names

mlp_net-weights-access: Set and retrieve (active) weights' values

mlp_plot: Plotting multilayer perceptron network

mlp_prune_mag: Minimum magnitude pruning

mlp_prune_obs: Optimal Brain Surgeon pruning

mlp_rm_neurons: Remove redundant neurons in a multilayer perceptron network

mlp_rnd_weights: This function sets network weights to random values drawn...

mlp_set_activation: Set network activation functions

mlp_teach_bp: Backpropagation (batch) teaching

mlp_teach_grprop: Rprop teaching - minimising arbitrary objective function

mlp_teach_rprop: Rprop teaching

mlp_teach_sa: Teaching networks using Simulated Annealing

mlp_teach_sgd: Stochastic gradient descent with (optional) RMS weights...

read-write-fcnndataset: Reading and writing datasets in the FCNN format

Functions

FCNN4R-package Man page
is.mlp_net Man page
mlp_actvfunc2str Man page
mlp_check_inout Man page
mlp_check_w Man page
mlp_eval Man page
mlp_expand_reorder_inputs Man page
mlp_export_C Man page
mlp_export_fcnn Man page
mlp_get_layers Man page
mlp_get_name Man page
mlp_get_no_active_w Man page
mlp_get_no_w Man page
mlp_get_w Man page
mlp_get_w_abs_idx Man page
mlp_get_weights Man page
mlp_get_w_idx Man page
mlp_get_w_st Man page
mlp_grad Man page
mlp_gradi Man page
mlp_gradij Man page
mlp_import_fcnn Man page
mlp_jacob Man page
mlp_merge Man page
mlp_mse Man page
mlp_net Man page
mlp_net-absolute-weight-indices Man page
mlp_net-accessing-individual-weights Man page
mlp_net-class Man page
mlp_net-combining-two-networks Man page
mlp_net-display Man page
mlp_net-export-import Man page
mlp_net-general-information Man page
mlp_net-manipulating-network-inputs Man page
mlp_net-method Man page
mlp_net-MSE-gradients Man page
mlp_net-names Man page
mlp_net-weights-access Man page
mlp_plot Man page
mlp_prune_mag Man page
mlp_prune_obs Man page
mlp_rm_input_neurons Man page
mlp_rm_neurons Man page
mlp_rnd_weights Man page
mlp_set_activation Man page
mlp_set_name Man page
mlp_set_w Man page
mlp_set_weights Man page
mlp_set_w_st Man page
mlp_stack Man page
mlp_teach_bp Man page
mlp_teach_grprop Man page
mlp_teach_rprop Man page
mlp_teach_sa Man page
mlp_teach_sgd Man page
print,mlp_net-method Man page
read.fcnndataset Man page
read-write-fcnndataset Man page
show,mlp_net-method Man page
summary,mlp_net-method Man page
write.fcnndataset Man page

Files

FCNN4R
FCNN4R/inst
FCNN4R/inst/CITATION
FCNN4R/src
FCNN4R/src/Makevars
FCNN4R/src/fcnn
FCNN4R/src/fcnn/level1.h
FCNN4R/src/fcnn/level2.h
FCNN4R/src/fcnn/fcnncfg.h
FCNN4R/src/fcnn/report.h
FCNN4R/src/fcnn/fcnncfg.R.h
FCNN4R/src/fcnn/level2.cpp
FCNN4R/src/fcnn/error.h
FCNN4R/src/fcnn/level1_impl.h
FCNN4R/src/fcnn/level3.h
FCNN4R/src/fcnn/struct.h
FCNN4R/src/fcnn/report.cpp
FCNN4R/src/fcnn/utils.h
FCNN4R/src/fcnn/utils.cpp
FCNN4R/src/fcnn/level3.cpp
FCNN4R/src/fcnn/activation.h
FCNN4R/src/fcnn/export.cpp
FCNN4R/src/fcnn/export.h
FCNN4R/src/fcnn/struct.cpp
FCNN4R/src/dataset.cpp
FCNN4R/src/Makevars.win
FCNN4R/src/interface.cpp
FCNN4R/NAMESPACE
FCNN4R/R
FCNN4R/R/mlp_prune.R FCNN4R/R/fcnn4r.R FCNN4R/R/mlp_net.R FCNN4R/R/mlp_gteach.R FCNN4R/R/mlp_teach.R FCNN4R/R/mlp_plot.R FCNN4R/R/dataset.R
FCNN4R/MD5
FCNN4R/DESCRIPTION
FCNN4R/man
FCNN4R/man/mlp_check_w.Rd FCNN4R/man/mlp_teach_rprop.Rd FCNN4R/man/mlp_net-combining-two-networks.Rd FCNN4R/man/mlp_net-absolute-weight-indices.Rd FCNN4R/man/mlp_net-manipulating-network-inputs.Rd FCNN4R/man/mlp_net-MSE-gradients.Rd FCNN4R/man/mlp_net-class.Rd FCNN4R/man/read-write-fcnndataset.Rd FCNN4R/man/mlp_teach_sa.Rd FCNN4R/man/mlp_net-export-import.Rd FCNN4R/man/mlp_set_activation.Rd FCNN4R/man/mlp_rnd_weights.Rd FCNN4R/man/mlp_actvfunc2str.Rd FCNN4R/man/mlp_rm_neurons.Rd FCNN4R/man/mlp_net-weights-access.Rd FCNN4R/man/mlp_teach_bp.Rd FCNN4R/man/mlp_export_C.Rd FCNN4R/man/mlp_net-display.Rd FCNN4R/man/mlp_plot.Rd FCNN4R/man/mlp_prune_obs.Rd FCNN4R/man/mlp_net-general-information.Rd FCNN4R/man/mlp_net.Rd FCNN4R/man/mlp_prune_mag.Rd FCNN4R/man/mlp_net-names.Rd FCNN4R/man/mlp_teach_sgd.Rd FCNN4R/man/mlp_net-accessing-individual-weights.Rd FCNN4R/man/mlp_check_inout.Rd FCNN4R/man/FCNN4R-package.Rd FCNN4R/man/mlp_eval.Rd FCNN4R/man/mlp_teach_grprop.Rd FCNN4R/man/is.mlp_net.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.