2 Fast Artificial Neural Network Library (fann)
3 Copyright (C) 2003 Steffen Nissen (lukesky@diku.dk)
5 This library is free software; you can redistribute it and/or
6 modify it under the terms of the GNU Lesser General Public
7 License as published by the Free Software Foundation; either
8 version 2.1 of the License, or (at your option) any later version.
10 This library is distributed in the hope that it will be useful,
11 but WITHOUT ANY WARRANTY; without even the implied warranty of
12 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
13 Lesser General Public License for more details.
15 You should have received a copy of the GNU Lesser General Public
16 License along with this library; if not, write to the Free Software
17 Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
20 #ifndef __fann_train_h__
21 #define __fann_train_h__
23 /* Section: FANN Training
25 There are many different ways of training neural networks and the FANN library supports
26 a number of different approaches.
28 Two fundementally different approaches are the most commonly used:
30 Fixed topology training - The size and topology of the ANN is determined in advance
31 and the training alters the weights in order to minimize the difference between
32 the desired output values and the actual output values. This kind of training is
33 supported by <fann_train_on_data>.
35 Evolving topology training - The training start out with an empty ANN, only consisting
36 of input and output neurons. Hidden neurons and connections is the added during training,
37 in order to reach the same goal as for fixed topology training. This kind of training
38 is supported by <FANN Cascade Training>.
41 /* Struct: struct fann_train_data
42 Structure used to store data, for use with training.
44 The data inside this structure should never be manipulated directly, but should use some
45 of the supplied functions in <Training Data Manipulation>.
47 The training data structure is very usefull for storing data during training and testing of a
51 <fann_read_train_from_file>, <fann_train_on_data>, <fann_destroy_train>
53 struct fann_train_data
55 enum fann_errno_enum errno_f;
59 unsigned int num_data;
60 unsigned int num_input;
61 unsigned int num_output;
66 /* Section: FANN Training */
71 /* Function: fann_train
73 Train one iteration with a set of inputs, and a set of desired outputs.
74 This training is always incremental training (see <fann_train_enum>), since
75 only one pattern is presented.
78 ann - The neural network structure
79 input - an array of inputs. This array must be exactly <fann_get_num_input> long.
80 desired_output - an array of desired outputs. This array must be exactly <fann_get_num_output> long.
83 <fann_train_on_data>, <fann_train_epoch>
85 This function appears in FANN >= 1.0.0.
87 FANN_EXTERNAL void FANN_API fann_train(struct fann *ann, fann_type * input,
88 fann_type * desired_output);
90 #endif /* NOT FIXEDFANN */
92 /* Function: fann_test
93 Test with a set of inputs, and a set of desired outputs.
94 This operation updates the mean square error, but does not
95 change the network in any way.
98 <fann_test_data>, <fann_train>
100 This function appears in FANN >= 1.0.0.
102 FANN_EXTERNAL fann_type * FANN_API fann_test(struct fann *ann, fann_type * input,
103 fann_type * desired_output);
105 /* Function: fann_get_MSE
106 Reads the mean square error from the network.
108 Reads the mean square error from the network. This value is calculated during
109 training or testing, and can therefore sometimes be a bit off if the weights
110 have been changed since the last calculation of the value.
115 This function appears in FANN >= 1.1.0.
117 FANN_EXTERNAL float FANN_API fann_get_MSE(struct fann *ann);
119 /* Function: fann_get_bit_fail
121 The number of fail bits; means the number of output neurons which differ more
122 than the bit fail limit (see <fann_get_bit_fail_limit>, <fann_set_bit_fail_limit>).
123 The bits are counted in all of the training data, so this number can be higher than
124 the number of training data.
126 This value is reset by <fann_reset_MSE> and updated by all the same functions which also
127 updates the MSE value (e.g. <fann_test_data>, <fann_train_epoch>)
130 <fann_stopfunc_enum>, <fann_get_MSE>
132 This function appears in FANN >= 2.0.0
134 FANN_EXTERNAL unsigned int fann_get_bit_fail(struct fann *ann);
136 /* Function: fann_reset_MSE
137 Resets the mean square error from the network.
139 This function also resets the number of bits that fail.
142 <fann_get_MSE>, <fann_get_bit_fail_limit>
144 This function appears in FANN >= 1.1.0
146 FANN_EXTERNAL void FANN_API fann_reset_MSE(struct fann *ann);
148 /* Group: Training Data Training */
152 /* Function: fann_train_on_data
154 Trains on an entire dataset, for a period of time.
156 This training uses the training algorithm chosen by <fann_set_training_algorithm>,
157 and the parameters set for these training algorithms.
160 ann - The neural network
161 data - The data, which should be used during training
162 max_epochs - The maximum number of epochs the training should continue
163 epochs_between_reports - The number of epochs between printing a status report to stdout.
164 A value of zero means no reports should be printed.
165 desired_error - The desired <fann_get_MSE> or <fann_get_bit_fail>, depending on which stop function
166 is chosen by <fann_set_train_stop_function>.
168 Instead of printing out reports every epochs_between_reports, a callback function can be called
169 (see <fann_set_callback>).
172 <fann_train_on_file>, <fann_train_epoch>, <Parameters>
174 This function appears in FANN >= 1.0.0.
176 FANN_EXTERNAL void FANN_API fann_train_on_data(struct fann *ann, struct fann_train_data *data,
177 unsigned int max_epochs,
178 unsigned int epochs_between_reports,
179 float desired_error);
181 /* Function: fann_train_on_file
183 Does the same as <fann_train_on_data>, but reads the training data directly from a file.
188 This function appears in FANN >= 1.0.0.
190 FANN_EXTERNAL void FANN_API fann_train_on_file(struct fann *ann, const char *filename,
191 unsigned int max_epochs,
192 unsigned int epochs_between_reports,
193 float desired_error);
195 /* Function: fann_train_epoch
196 Train one epoch with a set of training data.
198 Train one epoch with the training data stored in data. One epoch is where all of
199 the training data is considered exactly once.
201 This function returns the MSE error as it is calculated either before or during
202 the actual training. This is not the actual MSE after the training epoch, but since
203 calculating this will require to go through the entire training set once more, it is
204 more than adequate to use this value during training.
206 The training algorithm used by this function is chosen by the <fann_set_training_algorithm>
210 <fann_train_on_data>, <fann_test_data>
212 This function appears in FANN >= 1.2.0.
214 FANN_EXTERNAL float FANN_API fann_train_epoch(struct fann *ann, struct fann_train_data *data);
215 #endif /* NOT FIXEDFANN */
217 /* Function: fann_test_data
219 Test a set of training data and calculates the MSE for the training data.
221 This function updates the MSE and the bit fail values.
224 <fann_test>, <fann_get_MSE>, <fann_get_bit_fail>
226 This function appears in FANN >= 1.2.0.
228 FANN_EXTERNAL float FANN_API fann_test_data(struct fann *ann, struct fann_train_data *data);
230 /* Group: Training Data Manipulation */
232 /* Function: fann_read_train_from_file
233 Reads a file that stores training data.
235 The file must be formatted like:
236 >num_train_data num_input num_output
237 >inputdata seperated by space
238 >outputdata seperated by space
244 >inputdata seperated by space
245 >outputdata seperated by space
248 <fann_train_on_data>, <fann_destroy_train>, <fann_save_train>
250 This function appears in FANN >= 1.0.0
252 FANN_EXTERNAL struct fann_train_data *FANN_API fann_read_train_from_file(const char *filename);
255 /* Function: fann_destroy_train
256 Destructs the training data and properly deallocates all of the associated data.
257 Be sure to call this function after finished using the training data.
259 This function appears in FANN >= 1.0.0
261 FANN_EXTERNAL void FANN_API fann_destroy_train(struct fann_train_data *train_data);
264 /* Function: fann_shuffle_train_data
266 Shuffles training data, randomizing the order.
267 This is recommended for incremental training, while it have no influence during batch training.
269 This function appears in FANN >= 1.1.0.
271 FANN_EXTERNAL void FANN_API fann_shuffle_train_data(struct fann_train_data *train_data);
274 /* Function: fann_scale_input_train_data
276 Scales the inputs in the training data to the specified range.
279 <fann_scale_output_train_data>, <fann_scale_train_data>
281 This function appears in FANN >= 2.0.0.
283 FANN_EXTERNAL void FANN_API fann_scale_input_train_data(struct fann_train_data *train_data,
284 fann_type new_min, fann_type new_max);
287 /* Function: fann_scale_output_train_data
289 Scales the outputs in the training data to the specified range.
292 <fann_scale_input_train_data>, <fann_scale_train_data>
294 This function appears in FANN >= 2.0.0.
296 FANN_EXTERNAL void FANN_API fann_scale_output_train_data(struct fann_train_data *train_data,
297 fann_type new_min, fann_type new_max);
300 /* Function: fann_scale_train_data
302 Scales the inputs and outputs in the training data to the specified range.
305 <fann_scale_output_train_data>, <fann_scale_input_train_data>
307 This function appears in FANN >= 2.0.0.
309 FANN_EXTERNAL void FANN_API fann_scale_train_data(struct fann_train_data *train_data,
310 fann_type new_min, fann_type new_max);
313 /* Function: fann_merge_train_data
315 Merges the data from *data1* and *data2* into a new <struct fann_train_data>.
317 This function appears in FANN >= 1.1.0.
319 FANN_EXTERNAL struct fann_train_data *FANN_API fann_merge_train_data(struct fann_train_data *data1,
320 struct fann_train_data *data2);
323 /* Function: fann_duplicate_train_data
325 Returns an exact copy of a <struct fann_train_data>.
327 This function appears in FANN >= 1.1.0.
329 FANN_EXTERNAL struct fann_train_data *FANN_API fann_duplicate_train_data(struct fann_train_data
332 /* Function: fann_subset_train_data
334 Returns an copy of a subset of the <struct fann_train_data>, starting at position *pos*
335 and *length* elements forward.
337 >fann_subset_train_data(train_data, 0, fann_length_train_data(train_data))
339 Will do the same as <fann_duplicate_train_data>.
342 <fann_length_train_data>
344 This function appears in FANN >= 2.0.0.
346 FANN_EXTERNAL struct fann_train_data *FANN_API fann_subset_train_data(struct fann_train_data
347 *data, unsigned int pos,
348 unsigned int length);
350 /* Function: fann_length_train_data
352 Returns the number of training patterns in the <struct fann_train_data>.
354 This function appears in FANN >= 2.0.0.
356 FANN_EXTERNAL unsigned int FANN_API fann_length_train_data(struct fann_train_data *data);
358 /* Function: fann_num_input_train_data
360 Returns the number of inputs in each of the training patterns in the <struct fann_train_data>.
363 <fann_num_train_data>, <fann_num_output_train_data>
365 This function appears in FANN >= 2.0.0.
367 FANN_EXTERNAL unsigned int FANN_API fann_num_input_train_data(struct fann_train_data *data);
369 /* Function: fann_num_output_train_data
371 Returns the number of outputs in each of the training patterns in the <struct fann_train_data>.
374 <fann_num_train_data>, <fann_num_input_train_data>
376 This function appears in FANN >= 2.0.0.
378 FANN_EXTERNAL unsigned int FANN_API fann_num_output_train_data(struct fann_train_data *data);
380 /* Function: fann_save_train
382 Save the training structure to a file, with the format as specified in <fann_read_train_from_file>
385 The function returns 0 on success and -1 on failure.
388 <fann_read_train_from_file>, <fann_save_train_to_fixed>
390 This function appears in FANN >= 1.0.0.
392 FANN_EXTERNAL int FANN_API fann_save_train(struct fann_train_data *data, const char *filename);
395 /* Function: fann_save_train_to_fixed
397 Saves the training structure to a fixed point data file.
399 This function is very usefull for testing the quality of a fixed point network.
402 The function returns 0 on success and -1 on failure.
407 This function appears in FANN >= 1.0.0.
409 FANN_EXTERNAL int FANN_API fann_save_train_to_fixed(struct fann_train_data *data, const char *filename,
410 unsigned int decimal_point);
413 /* Group: Parameters */
415 /* Function: fann_get_training_algorithm
417 Return the training algorithm as described by <fann_train_enum>. This training algorithm
418 is used by <fann_train_on_data> and associated functions.
420 Note that this algorithm is also used during <fann_cascadetrain_on_data>, although only
421 FANN_TRAIN_RPROP and FANN_TRAIN_QUICKPROP is allowed during cascade training.
423 The default training algorithm is FANN_TRAIN_RPROP.
426 <fann_set_training_algorithm>, <fann_train_enum>
428 This function appears in FANN >= 1.0.0.
430 FANN_EXTERNAL enum fann_train_enum FANN_API fann_get_training_algorithm(struct fann *ann);
433 /* Function: fann_set_training_algorithm
435 Set the training algorithm.
437 More info available in <fann_get_training_algorithm>
439 This function appears in FANN >= 1.0.0.
441 FANN_EXTERNAL void FANN_API fann_set_training_algorithm(struct fann *ann,
442 enum fann_train_enum training_algorithm);
445 /* Function: fann_get_learning_rate
447 Return the learning rate.
449 The learning rate is used to determine how aggressive training should be for some of the
450 training algorithms (FANN_TRAIN_INCREMENTAL, FANN_TRAIN_BATCH, FANN_TRAIN_QUICKPROP).
451 Do however note that it is not used in FANN_TRAIN_RPROP.
453 The default learning rate is 0.7.
456 <fann_set_learning_rate>, <fann_set_training_algorithm>
458 This function appears in FANN >= 1.0.0.
460 FANN_EXTERNAL float FANN_API fann_get_learning_rate(struct fann *ann);
463 /* Function: fann_set_learning_rate
465 Set the learning rate.
467 More info available in <fann_get_learning_rate>
469 This function appears in FANN >= 1.0.0.
471 FANN_EXTERNAL void FANN_API fann_set_learning_rate(struct fann *ann, float learning_rate);
473 /* Function: fann_get_learning_momentum
475 Get the learning momentum.
477 The learning momentum can be used to speed up FANN_TRAIN_INCREMENTAL training.
478 A too high momentum will however not benefit training. Setting momentum to 0 will
479 be the same as not using the momentum parameter. The recommended value of this parameter
480 is between 0.0 and 1.0.
482 The default momentum is 0.
485 <fann_set_learning_momentum>, <fann_set_training_algorithm>
487 This function appears in FANN >= 2.0.0.
489 FANN_EXTERNAL float FANN_API fann_get_learning_momentum(struct fann *ann);
492 /* Function: fann_set_learning_momentum
494 Set the learning momentum.
496 More info available in <fann_get_learning_momentum>
498 This function appears in FANN >= 2.0.0.
500 FANN_EXTERNAL void FANN_API fann_set_learning_momentum(struct fann *ann, float learning_momentum);
503 /* Function: fann_set_activation_function
505 Set the activation function for neuron number *neuron* in layer number *layer*,
506 counting the input layer as layer 0.
508 It is not possible to set activation functions for the neurons in the input layer.
510 When choosing an activation function it is important to note that the activation
511 functions have different range. FANN_SIGMOID is e.g. in the 0 - 1 range while
512 FANN_SIGMOID_SYMMETRIC is in the -1 - 1 range and FANN_LINEAR is unbound.
514 Information about the individual activation functions is available at <fann_activationfunc_enum>.
516 The default activation function is FANN_SIGMOID_STEPWISE.
519 <fann_set_activation_function_layer>, <fann_set_activation_function_hidden>,
520 <fann_set_activation_function_output>, <fann_set_activation_steepness>
522 This function appears in FANN >= 2.0.0.
524 FANN_EXTERNAL void FANN_API fann_set_activation_function(struct fann *ann,
525 enum fann_activationfunc_enum
530 /* Function: fann_set_activation_function_layer
532 Set the activation function for all the neurons in the layer number *layer*,
533 counting the input layer as layer 0.
535 It is not possible to set activation functions for the neurons in the input layer.
538 <fann_set_activation_function>, <fann_set_activation_function_hidden>,
539 <fann_set_activation_function_output>, <fann_set_activation_steepness_layer>
541 This function appears in FANN >= 2.0.0.
543 FANN_EXTERNAL void FANN_API fann_set_activation_function_layer(struct fann *ann,
544 enum fann_activationfunc_enum
548 /* Function: fann_set_activation_function_hidden
550 Set the activation function for all of the hidden layers.
553 <fann_set_activation_function>, <fann_set_activation_function_layer>,
554 <fann_set_activation_function_output>, <fann_set_activation_steepness_hidden>
556 This function appears in FANN >= 1.0.0.
558 FANN_EXTERNAL void FANN_API fann_set_activation_function_hidden(struct fann *ann,
559 enum fann_activationfunc_enum
560 activation_function);
563 /* Function: fann_set_activation_function_output
565 Set the activation function for the output layer.
568 <fann_set_activation_function>, <fann_set_activation_function_layer>,
569 <fann_set_activation_function_hidden>, <fann_set_activation_steepness_output>
571 This function appears in FANN >= 1.0.0.
573 FANN_EXTERNAL void FANN_API fann_set_activation_function_output(struct fann *ann,
574 enum fann_activationfunc_enum
575 activation_function);
577 /* Function: fann_set_activation_steepness
579 Set the activation steepness for neuron number *neuron* in layer number *layer*,
580 counting the input layer as layer 0.
582 It is not possible to set activation steepness for the neurons in the input layer.
584 The steepness of an activation function says something about how fast the activation function
585 goes from the minimum to the maximum. A high value for the activation function will also
586 give a more agressive training.
588 When training neural networks where the output values should be at the extremes (usually 0 and 1,
589 depending on the activation function), a steep activation function can be used (e.g. 1.0).
591 The default activation steepness is 0.5.
594 <fann_set_activation_steepness_layer>, <fann_set_activation_steepness_hidden>,
595 <fann_set_activation_steepness_output>, <fann_set_activation_function>
597 This function appears in FANN >= 2.0.0.
599 FANN_EXTERNAL void FANN_API fann_set_activation_steepness(struct fann *ann,
604 /* Function: fann_set_activation_steepness_layer
606 Set the activation steepness all of the neurons in layer number *layer*,
607 counting the input layer as layer 0.
609 It is not possible to set activation steepness for the neurons in the input layer.
612 <fann_set_activation_steepness>, <fann_set_activation_steepness_hidden>,
613 <fann_set_activation_steepness_output>, <fann_set_activation_function_layer>
615 This function appears in FANN >= 2.0.0.
617 FANN_EXTERNAL void FANN_API fann_set_activation_steepness_layer(struct fann *ann,
621 /* Function: fann_set_activation_steepness_hidden
623 Set the steepness of the activation steepness in all of the hidden layers.
626 <fann_set_activation_steepness>, <fann_set_activation_steepness_layer>,
627 <fann_set_activation_steepness_output>, <fann_set_activation_function_hidden>
629 This function appears in FANN >= 1.2.0.
631 FANN_EXTERNAL void FANN_API fann_set_activation_steepness_hidden(struct fann *ann,
632 fann_type steepness);
635 /* Function: fann_set_activation_steepness_output
637 Set the steepness of the activation steepness in the output layer.
640 <fann_set_activation_steepness>, <fann_set_activation_steepness_layer>,
641 <fann_set_activation_steepness_hidden>, <fann_set_activation_function_output>
643 This function appears in FANN >= 1.2.0.
645 FANN_EXTERNAL void FANN_API fann_set_activation_steepness_output(struct fann *ann,
646 fann_type steepness);
649 /* Function: fann_get_train_error_function
651 Returns the error function used during training.
653 The error functions is described further in <fann_errorfunc_enum>
655 The default error function is FANN_ERRORFUNC_TANH
658 <fann_set_train_error_function>
660 This function appears in FANN >= 1.2.0.
662 FANN_EXTERNAL enum fann_errorfunc_enum FANN_API fann_get_train_error_function(struct fann *ann);
665 /* Function: fann_set_train_error_function
667 Set the error function used during training.
669 The error functions is described further in <fann_errorfunc_enum>
672 <fann_get_train_error_function>
674 This function appears in FANN >= 1.2.0.
676 FANN_EXTERNAL void FANN_API fann_set_train_error_function(struct fann *ann,
677 enum fann_errorfunc_enum
678 train_error_function);
681 /* Function: fann_get_train_stop_function
683 Returns the the stop function used during training.
685 The stop function is described further in <fann_stopfunc_enum>
687 The default stop function is FANN_STOPFUNC_MSE
690 <fann_get_train_stop_function>, <fann_get_bit_fail_limit>
692 This function appears in FANN >= 2.0.0.
694 FANN_EXTERNAL enum fann_stopfunc_enum FANN_API fann_get_train_stop_function(struct fann *ann);
697 /* Function: fann_set_train_stop_function
699 Set the stop function used during training.
701 Returns the the stop function used during training.
703 The stop function is described further in <fann_stopfunc_enum>
706 <fann_get_train_stop_function>
708 This function appears in FANN >= 2.0.0.
710 FANN_EXTERNAL void FANN_API fann_set_train_stop_function(struct fann *ann,
711 enum fann_stopfunc_enum train_stop_function);
714 /* Function: fann_get_bit_fail_limit
716 Returns the bit fail limit used during training.
718 The bit fail limit is used during training where the <fann_stopfunc_enum> is set to FANN_STOPFUNC_BIT.
720 The limit is the maximum accepted difference between the desired output and the actual output during
721 training. Each output that diverges more than this limit is counted as an error bit.
722 This difference is divided by two when dealing with symmetric activation functions,
723 so that symmetric and not symmetric activation functions can use the same limit.
725 The default bit fail limit is 0.35.
728 <fann_set_bit_fail_limit>
730 This function appears in FANN >= 2.0.0.
732 FANN_EXTERNAL fann_type FANN_API fann_get_bit_fail_limit(struct fann *ann);
734 /* Function: fann_set_bit_fail_limit
736 Set the bit fail limit used during training.
739 <fann_get_bit_fail_limit>
741 This function appears in FANN >= 2.0.0.
743 FANN_EXTERNAL void FANN_API fann_set_bit_fail_limit(struct fann *ann, fann_type bit_fail_limit);
745 /* Function: fann_set_callback
747 Sets the callback function for use during training.
749 See <fann_callback_type> for more information about the callback function.
751 The default callback function simply prints out some status information.
753 This function appears in FANN >= 2.0.0.
755 FANN_EXTERNAL void FANN_API fann_set_callback(struct fann *ann, fann_callback_type callback);
757 /* Function: fann_get_quickprop_decay
759 The decay is a small negative valued number which is the factor that the weights
760 should become smaller in each iteration during quickprop training. This is used
761 to make sure that the weights do not become too high during training.
763 The default decay is -0.0001.
766 <fann_set_quickprop_decay>
768 This function appears in FANN >= 1.2.0.
770 FANN_EXTERNAL float FANN_API fann_get_quickprop_decay(struct fann *ann);
773 /* Function: fann_set_quickprop_decay
775 Sets the quickprop decay factor.
778 <fann_get_quickprop_decay>
780 This function appears in FANN >= 1.2.0.
782 FANN_EXTERNAL void FANN_API fann_set_quickprop_decay(struct fann *ann, float quickprop_decay);
785 /* Function: fann_get_quickprop_mu
787 The mu factor is used to increase and decrease the step-size during quickprop training.
788 The mu factor should always be above 1, since it would otherwise decrease the step-size
789 when it was suppose to increase it.
791 The default mu factor is 1.75.
794 <fann_set_quickprop_mu>
796 This function appears in FANN >= 1.2.0.
798 FANN_EXTERNAL float FANN_API fann_get_quickprop_mu(struct fann *ann);
801 /* Function: fann_set_quickprop_mu
803 Sets the quickprop mu factor.
806 <fann_get_quickprop_mu>
808 This function appears in FANN >= 1.2.0.
810 FANN_EXTERNAL void FANN_API fann_set_quickprop_mu(struct fann *ann, float quickprop_mu);
813 /* Function: fann_get_rprop_increase_factor
815 The increase factor is a value larger than 1, which is used to
816 increase the step-size during RPROP training.
818 The default increase factor is 1.2.
821 <fann_set_rprop_increase_factor>
823 This function appears in FANN >= 1.2.0.
825 FANN_EXTERNAL float FANN_API fann_get_rprop_increase_factor(struct fann *ann);
828 /* Function: fann_set_rprop_increase_factor
830 The increase factor used during RPROP training.
833 <fann_get_rprop_increase_factor>
835 This function appears in FANN >= 1.2.0.
837 FANN_EXTERNAL void FANN_API fann_set_rprop_increase_factor(struct fann *ann,
838 float rprop_increase_factor);
841 /* Function: fann_get_rprop_decrease_factor
843 The decrease factor is a value smaller than 1, which is used to decrease the step-size during RPROP training.
845 The default decrease factor is 0.5.
848 <fann_set_rprop_decrease_factor>
850 This function appears in FANN >= 1.2.0.
852 FANN_EXTERNAL float FANN_API fann_get_rprop_decrease_factor(struct fann *ann);
855 /* Function: fann_set_rprop_decrease_factor
857 The decrease factor is a value smaller than 1, which is used to decrease the step-size during RPROP training.
860 <fann_get_rprop_decrease_factor>
862 This function appears in FANN >= 1.2.0.
864 FANN_EXTERNAL void FANN_API fann_set_rprop_decrease_factor(struct fann *ann,
865 float rprop_decrease_factor);
868 /* Function: fann_get_rprop_delta_min
870 The minimum step-size is a small positive number determining how small the minimum step-size may be.
872 The default value delta min is 0.0.
875 <fann_set_rprop_delta_min>
877 This function appears in FANN >= 1.2.0.
879 FANN_EXTERNAL float FANN_API fann_get_rprop_delta_min(struct fann *ann);
882 /* Function: fann_set_rprop_delta_min
884 The minimum step-size is a small positive number determining how small the minimum step-size may be.
887 <fann_get_rprop_delta_min>
889 This function appears in FANN >= 1.2.0.
891 FANN_EXTERNAL void FANN_API fann_set_rprop_delta_min(struct fann *ann, float rprop_delta_min);
894 /* Function: fann_get_rprop_delta_max
896 The maximum step-size is a positive number determining how large the maximum step-size may be.
898 The default delta max is 50.0.
901 <fann_set_rprop_delta_max>, <fann_get_rprop_delta_min>
903 This function appears in FANN >= 1.2.0.
905 FANN_EXTERNAL float FANN_API fann_get_rprop_delta_max(struct fann *ann);
908 /* Function: fann_set_rprop_delta_max
910 The maximum step-size is a positive number determining how large the maximum step-size may be.
913 <fann_get_rprop_delta_max>, <fann_get_rprop_delta_min>
915 This function appears in FANN >= 1.2.0.
917 FANN_EXTERNAL void FANN_API fann_set_rprop_delta_max(struct fann *ann, float rprop_delta_max);