--- /dev/null
+/*
+Fast Artificial Neural Network Library (fann)
+Copyright (C) 2003 Steffen Nissen (lukesky@diku.dk)
+
+This library is free software; you can redistribute it and/or
+modify it under the terms of the GNU Lesser General Public
+License as published by the Free Software Foundation; either
+version 2.1 of the License, or (at your option) any later version.
+
+This library is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+Lesser General Public License for more details.
+
+You should have received a copy of the GNU Lesser General Public
+License along with this library; if not, write to the Free Software
+Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
+*/
+
+#ifndef __fann_cascade_h__
+#define __fann_cascade_h__
+
+/* Section: FANN Cascade Training
+ Cascade training differs from ordinary training in the sense that it starts with an empty neural network
+ and then adds neurons one by one, while it trains the neural network. The main benefit of this approach,
+ is that you do not have to guess the number of hidden layers and neurons prior to training, but cascade
+ training have also proved better at solving some problems.
+
+ The basic idea of cascade training is that a number of candidate neurons are trained separate from the
+ real network, then the most promissing of these candidate neurons is inserted into the neural network.
+ Then the output connections are trained and new candidate neurons is prepared. The candidate neurons are
+ created as shorcut connected neurons in a new hidden layer, which means that the final neural network
+ will consist of a number of hidden layers with one shorcut connected neuron in each.
+*/
+
+/* Group: Cascade Training */
+
+/* Function: fann_cascadetrain_on_data
+
+ Trains on an entire dataset, for a period of time using the Cascade2 training algorithm.
+ This algorithm adds neurons to the neural network while training, which means that it
+ needs to start with an ANN without any hidden layers. The neural network should also use
+ shortcut connections, so <fann_create_shortcut> should be used to create the ANN like this:
+ >struct fann *ann = fann_create_shortcut(2, fann_num_input_train_data(train_data), fann_num_input_train_data(train_data));
+
+ This training uses the parameters set using the fann_set_cascade_..., but it also uses another
+ training algorithm as it's internal training algorithm. This algorithm can be set to either
+ FANN_TRAIN_RPROP or FANN_TRAIN_QUICKPROP by <fann_set_training_algorithm>, and the parameters
+ set for these training algorithms will also affect the cascade training.
+
+ Parameters:
+ ann - The neural network
+ data - The data, which should be used during training
+ max_neuron - The maximum number of neurons to be added to neural network
+ neurons_between_reports - The number of neurons between printing a status report to stdout.
+ A value of zero means no reports should be printed.
+ desired_error - The desired <fann_get_MSE> or <fann_get_bit_fail>, depending on which stop function
+ is chosen by <fann_set_train_stop_function>.
+
+ Instead of printing out reports every neurons_between_reports, a callback function can be called
+ (see <fann_set_callback>).
+
+ See also:
+ <fann_train_on_data>, <fann_cascadetrain_on_file>, <Parameters>
+
+ This function appears in FANN >= 2.0.0.
+*/
+FANN_EXTERNAL void FANN_API fann_cascadetrain_on_data(struct fann *ann,
+ struct fann_train_data *data,
+ unsigned int max_neurons,
+ unsigned int neurons_between_reports,
+ float desired_error);
+
+/* Function: fann_cascadetrain_on_file
+
+ Does the same as <fann_cascadetrain_on_data>, but reads the training data directly from a file.
+
+ See also:
+ <fann_cascadetrain_on_data>
+
+ This function appears in FANN >= 2.0.0.
+*/
+FANN_EXTERNAL void FANN_API fann_cascadetrain_on_file(struct fann *ann, const char *filename,
+ unsigned int max_neurons,
+ unsigned int neurons_between_reports,
+ float desired_error);
+
+/* Group: Parameters */
+
+/* Function: fann_get_cascade_output_change_fraction
+
+ The cascade output change fraction is a number between 0 and 1 determining how large a fraction
+ the <fann_get_MSE> value should change within <fann_get_cascade_output_stagnation_epochs> during
+ training of the output connections, in order for the training not to stagnate. If the training
+ stagnates, the training of the output connections will be ended and new candidates will be prepared.
+
+ This means:
+ If the MSE does not change by a fraction of <fann_get_cascade_output_change_fraction> during a
+ period of <fann_get_cascade_output_stagnation_epochs>, the training of the output connections
+ is stopped because the training has stagnated.
+
+ If the cascade output change fraction is low, the output connections will be trained more and if the
+ fraction is high they will be trained less.
+
+ The default cascade output change fraction is 0.01, which is equalent to a 1% change in MSE.
+
+ See also:
+ <fann_set_cascade_output_change_fraction>, <fann_get_MSE>, <fann_get_cascade_output_stagnation_epochs>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL float FANN_API fann_get_cascade_output_change_fraction(struct fann *ann);
+
+
+/* Function: fann_set_cascade_output_change_fraction
+
+ Sets the cascade output change fraction.
+
+ See also:
+ <fann_get_cascade_output_change_fraction>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL void FANN_API fann_set_cascade_output_change_fraction(struct fann *ann,
+ float cascade_output_change_fraction);
+
+/* Function: fann_get_cascade_output_stagnation_epochs
+
+ The number of cascade output stagnation epochs determines the number of epochs training is allowed to
+ continue without changing the MSE by a fraction of <fann_get_cascade_output_change_fraction>.
+
+ See more info about this parameter in <fann_get_cascade_output_change_fraction>.
+
+ The default number of cascade output stagnation epochs is 12.
+
+ See also:
+ <fann_set_cascade_output_stagnation_epochs>, <fann_get_cascade_output_change_fraction>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL unsigned int FANN_API fann_get_cascade_output_stagnation_epochs(struct fann *ann);
+
+
+/* Function: fann_set_cascade_output_stagnation_epochs
+
+ Sets the number of cascade output stagnation epochs.
+
+ See also:
+ <fann_get_cascade_output_stagnation_epochs>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL void FANN_API fann_set_cascade_output_stagnation_epochs(struct fann *ann,
+ unsigned int cascade_output_stagnation_epochs);
+
+
+/* Function: fann_get_cascade_candidate_change_fraction
+
+ The cascade candidate change fraction is a number between 0 and 1 determining how large a fraction
+ the <fann_get_MSE> value should change within <fann_get_cascade_candidate_stagnation_epochs> during
+ training of the candidate neurons, in order for the training not to stagnate. If the training
+ stagnates, the training of the candidate neurons will be ended and the best candidate will be selected.
+
+ This means:
+ If the MSE does not change by a fraction of <fann_get_cascade_candidate_change_fraction> during a
+ period of <fann_get_cascade_candidate_stagnation_epochs>, the training of the candidate neurons
+ is stopped because the training has stagnated.
+
+ If the cascade candidate change fraction is low, the candidate neurons will be trained more and if the
+ fraction is high they will be trained less.
+
+ The default cascade candidate change fraction is 0.01, which is equalent to a 1% change in MSE.
+
+ See also:
+ <fann_set_cascade_candidate_change_fraction>, <fann_get_MSE>, <fann_get_cascade_candidate_stagnation_epochs>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL float FANN_API fann_get_cascade_candidate_change_fraction(struct fann *ann);
+
+
+/* Function: fann_set_cascade_candidate_change_fraction
+
+ Sets the cascade candidate change fraction.
+
+ See also:
+ <fann_get_cascade_candidate_change_fraction>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL void FANN_API fann_set_cascade_candidate_change_fraction(struct fann *ann,
+ float cascade_candidate_change_fraction);
+
+/* Function: fann_get_cascade_candidate_stagnation_epochs
+
+ The number of cascade candidate stagnation epochs determines the number of epochs training is allowed to
+ continue without changing the MSE by a fraction of <fann_get_cascade_candidate_change_fraction>.
+
+ See more info about this parameter in <fann_get_cascade_candidate_change_fraction>.
+
+ The default number of cascade candidate stagnation epochs is 12.
+
+ See also:
+ <fann_set_cascade_candidate_stagnation_epochs>, <fann_get_cascade_candidate_change_fraction>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL unsigned int FANN_API fann_get_cascade_candidate_stagnation_epochs(struct fann *ann);
+
+
+/* Function: fann_set_cascade_candidate_stagnation_epochs
+
+ Sets the number of cascade candidate stagnation epochs.
+
+ See also:
+ <fann_get_cascade_candidate_stagnation_epochs>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL void FANN_API fann_set_cascade_candidate_stagnation_epochs(struct fann *ann,
+ unsigned int cascade_candidate_stagnation_epochs);
+
+
+/* Function: fann_get_cascade_weight_multiplier
+
+ The weight multiplier is a parameter which is used to multiply the weights from the candidate neuron
+ before adding the neuron to the neural network. This parameter is usually between 0 and 1, and is used
+ to make the training a bit less aggressive.
+
+ The default weight multiplier is 0.4
+
+ See also:
+ <fann_set_cascade_weight_multiplier>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL fann_type FANN_API fann_get_cascade_weight_multiplier(struct fann *ann);
+
+
+/* Function: fann_set_cascade_weight_multiplier
+
+ Sets the weight multiplier.
+
+ See also:
+ <fann_get_cascade_weight_multiplier>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL void FANN_API fann_set_cascade_weight_multiplier(struct fann *ann,
+ fann_type cascade_weight_multiplier);
+
+
+/* Function: fann_get_cascade_candidate_limit
+
+ The candidate limit is a limit for how much the candidate neuron may be trained.
+ The limit is a limit on the proportion between the MSE and candidate score.
+
+ Set this to a lower value to avoid overfitting and to a higher if overfitting is
+ not a problem.
+
+ The default candidate limit is 1000.0
+
+ See also:
+ <fann_set_cascade_candidate_limit>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL fann_type FANN_API fann_get_cascade_candidate_limit(struct fann *ann);
+
+
+/* Function: fann_set_cascade_candidate_limit
+
+ Sets the candidate limit.
+
+ See also:
+ <fann_get_cascade_candidate_limit>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL void FANN_API fann_set_cascade_candidate_limit(struct fann *ann,
+ fann_type cascade_candidate_limit);
+
+
+/* Function: fann_get_cascade_max_out_epochs
+
+ The maximum out epochs determines the maximum number of epochs the output connections
+ may be trained after adding a new candidate neuron.
+
+ The default max out epochs is 150
+
+ See also:
+ <fann_set_cascade_max_out_epochs>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL unsigned int FANN_API fann_get_cascade_max_out_epochs(struct fann *ann);
+
+
+/* Function: fann_set_cascade_max_out_epochs
+
+ Sets the maximum out epochs.
+
+ See also:
+ <fann_get_cascade_max_out_epochs>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL void FANN_API fann_set_cascade_max_out_epochs(struct fann *ann,
+ unsigned int cascade_max_out_epochs);
+
+
+/* Function: fann_get_cascade_max_cand_epochs
+
+ The maximum candidate epochs determines the maximum number of epochs the input
+ connections to the candidates may be trained before adding a new candidate neuron.
+
+ The default max candidate epochs is 150
+
+ See also:
+ <fann_set_cascade_max_cand_epochs>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL unsigned int FANN_API fann_get_cascade_max_cand_epochs(struct fann *ann);
+
+
+/* Function: fann_set_cascade_max_cand_epochs
+
+ Sets the max candidate epochs.
+
+ See also:
+ <fann_get_cascade_max_cand_epochs>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL void FANN_API fann_set_cascade_max_cand_epochs(struct fann *ann,
+ unsigned int cascade_max_cand_epochs);
+
+
+/* Function: fann_get_cascade_num_candidates
+
+ The number of candidates used during training (calculated by multiplying <fann_get_cascade_activation_functions_count>,
+ <fann_get_cascade_activation_steepnesses_count> and <fann_get_cascade_num_candidate_groups>).
+
+ The actual candidates is defined by the <fann_get_cascade_activation_functions> and
+ <fann_get_cascade_activation_steepnesses> arrays. These arrays define the activation functions
+ and activation steepnesses used for the candidate neurons. If there are 2 activation functions
+ in the activation function array and 3 steepnesses in the steepness array, then there will be
+ 2x3=6 different candidates which will be trained. These 6 different candidates can be copied into
+ several candidate groups, where the only difference between these groups is the initial weights.
+ If the number of groups is set to 2, then the number of candidate neurons will be 2x3x2=12. The
+ number of candidate groups is defined by <fann_set_cascade_num_candidate_groups>.
+
+ The default number of candidates is 6x4x2 = 48
+
+ See also:
+ <fann_get_cascade_activation_functions>, <fann_get_cascade_activation_functions_count>,
+ <fann_get_cascade_activation_steepnesses>, <fann_get_cascade_activation_steepnesses_count>,
+ <fann_get_cascade_num_candidate_groups>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL unsigned int FANN_API fann_get_cascade_num_candidates(struct fann *ann);
+
+/* Function: fann_get_cascade_activation_functions_count
+
+ The number of activation functions in the <fann_get_cascade_activation_functions> array.
+
+ The default number of activation functions is 6.
+
+ See also:
+ <fann_get_cascade_activation_functions>, <fann_set_cascade_activation_functions>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL unsigned int FANN_API fann_get_cascade_activation_functions_count(struct fann *ann);
+
+
+/* Function: fann_get_cascade_activation_functions
+
+ The cascade activation functions array is an array of the different activation functions used by
+ the candidates.
+
+ See <fann_get_cascade_num_candidates> for a description of which candidate neurons will be
+ generated by this array.
+
+ The default activation functions is {FANN_SIGMOID, FANN_SIGMOID_SYMMETRIC, FANN_GAUSSIAN, FANN_GAUSSIAN_SYMMETRIC, FANN_ELLIOT, FANN_ELLIOT_SYMMETRIC}
+
+ See also:
+ <fann_get_cascade_activation_functions_count>, <fann_set_cascade_activation_functions>,
+ <fann_activationfunc_enum>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL enum fann_activationfunc_enum * FANN_API fann_get_cascade_activation_functions(
+ struct fann *ann);
+
+
+/* Function: fann_set_cascade_activation_functions
+
+ Sets the array of cascade candidate activation functions. The array must be just as long
+ as defined by the count.
+
+ See <fann_get_cascade_num_candidates> for a description of which candidate neurons will be
+ generated by this array.
+
+ See also:
+ <fann_get_cascade_activation_steepnesses_count>, <fann_get_cascade_activation_steepnesses>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL void fann_set_cascade_activation_functions(struct fann *ann,
+ enum fann_activationfunc_enum *
+ cascade_activation_functions,
+ unsigned int
+ cascade_activation_functions_count);
+
+
+/* Function: fann_get_cascade_activation_steepnesses_count
+
+ The number of activation steepnesses in the <fann_get_cascade_activation_functions> array.
+
+ The default number of activation steepnesses is 4.
+
+ See also:
+ <fann_get_cascade_activation_steepnesses>, <fann_set_cascade_activation_functions>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL unsigned int FANN_API fann_get_cascade_activation_steepnesses_count(struct fann *ann);
+
+
+/* Function: fann_get_cascade_activation_steepnesses
+
+ The cascade activation steepnesses array is an array of the different activation functions used by
+ the candidates.
+
+ See <fann_get_cascade_num_candidates> for a description of which candidate neurons will be
+ generated by this array.
+
+ The default activation steepnesses is {0.25, 0.50, 0.75, 1.00}
+
+ See also:
+ <fann_set_cascade_activation_steepnesses>, <fann_get_cascade_activation_steepnesses_count>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL fann_type * FANN_API fann_get_cascade_activation_steepnesses(struct fann *ann);
+
+
+/* Function: fann_set_cascade_activation_steepnesses
+
+ Sets the array of cascade candidate activation steepnesses. The array must be just as long
+ as defined by the count.
+
+ See <fann_get_cascade_num_candidates> for a description of which candidate neurons will be
+ generated by this array.
+
+ See also:
+ <fann_get_cascade_activation_steepnesses>, <fann_get_cascade_activation_steepnesses_count>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL void fann_set_cascade_activation_steepnesses(struct fann *ann,
+ fann_type *
+ cascade_activation_steepnesses,
+ unsigned int
+ cascade_activation_steepnesses_count);
+
+/* Function: fann_get_cascade_num_candidate_groups
+
+ The number of candidate groups is the number of groups of identical candidates which will be used
+ during training.
+
+ This number can be used to have more candidates without having to define new parameters for the candidates.
+
+ See <fann_get_cascade_num_candidates> for a description of which candidate neurons will be
+ generated by this parameter.
+
+ The default number of candidate groups is 2
+
+ See also:
+ <fann_set_cascade_num_candidate_groups>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL unsigned int FANN_API fann_get_cascade_num_candidate_groups(struct fann *ann);
+
+
+/* Function: fann_set_cascade_num_candidate_groups
+
+ Sets the number of candidate groups.
+
+ See also:
+ <fann_get_cascade_num_candidate_groups>
+
+ This function appears in FANN >= 2.0.0.
+ */
+FANN_EXTERNAL void FANN_API fann_set_cascade_num_candidate_groups(struct fann *ann,
+ unsigned int cascade_num_candidate_groups);
+
+
+#endif
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