AI-FANN

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FANN.xs  view on Meta::CPAN

    struct fann *self;
    struct fann_train_data *data;
    unsigned int max_epochs;
    unsigned int epochs_between_reports;
    double desired_error;
  CLEANUP:
    _check_error(aTHX_ (struct fann_error *)self);
    _check_error(aTHX_ (struct fann_error *)data);

void
fann_cascadetrain_on_file(self, filename, max_neurons, neurons_between_reports, desired_error)
    struct fann *self;
	const char *filename;
    unsigned int max_neurons;
    unsigned int neurons_between_reports;
    double desired_error;
  CLEANUP:
    _check_error(aTHX_ (struct fann_error *)self);

void
fann_cascadetrain_on_data(self, data, max_neurons, neurons_between_reports, desired_error)
    struct fann *self;
    struct fann_train_data *data;
    unsigned int max_neurons;
    unsigned int neurons_between_reports;
    double desired_error;
  CLEANUP:
    _check_error(aTHX_ (struct fann_error *)self);
    _check_error(aTHX_ (struct fann_error *)data);

double

FANN.xs  view on Meta::CPAN

void
fann_print_connections(self)
    struct fann * self;

void
fann_print_parameters(self)
    struct fann * self;

void
fann_cascade_activation_functions(self, ...)
    struct fann *self;
  PREINIT:
    unsigned int count;
  PPCODE:
    if (items > 1) {
        unsigned int i;
        enum fann_activationfunc_enum * funcs;
        count = items - 1;
        Newx(funcs, items - 1, enum fann_activationfunc_enum);
        SAVEFREEPV(funcs);
        for (i = 0; i < count; i++) {
            funcs[i] = _sv2fann_activationfunc_enum(ST(i+1));
        }
        fann_set_cascade_activation_functions(self, funcs, count);
    }
    count = fann_get_cascade_activation_functions_count(self);
    if (GIMME_V == G_ARRAY) {
        unsigned int i;
        enum fann_activationfunc_enum * funcs = fann_get_cascade_activation_functions(self);
        EXTEND(SP, count);
        for (i = 0; i < count; i++) {
            ST(i) = sv_2mortal(_fann_activationfunc_enum2sv(funcs[i]));
        }
        XSRETURN(count);
    }
    else {
        ST(0) = sv_2mortal(newSVuv(count));
        XSRETURN(1);
    }

void
fann_cascade_activation_steepnesses(self, ...)
    struct fann *self;
  PREINIT:
    unsigned int count;
  PPCODE:
    if (items > 1) {
        unsigned int i;
        fann_type * steepnesses;
        count = items - 1;
        Newx(steepnesses, items - 1, fann_type);
        SAVEFREEPV(steepnesses);
        for (i = 0; i < count; i++) {
            steepnesses[i] = SvNV(ST(i+1));
        }
        fann_set_cascade_activation_steepnesses(self, steepnesses, count);
    }
    count = fann_get_cascade_activation_steepnesses_count(self);
    if (GIMME_V == G_ARRAY) {
        unsigned int i;
        fann_type * steepnesses = fann_get_cascade_activation_steepnesses(self);
        EXTEND(SP, count);
        for (i = 0; i < count; i++) {
            ST(i) = sv_2mortal(newSVuv(steepnesses[i]));
        }
        XSRETURN(count);
    }
    else {
        ST(0) = sv_2mortal(newSVuv(count));
        XSRETURN(1);
    }

accessors.xsh  view on Meta::CPAN

    RETVAL = fann_get_bit_fail(self);
  OUTPUT:
    RETVAL
  CLEANUP:
    _check_error(aTHX_ (struct fann_error *)self);


MODULE = AI::FANN    PACKAGE = AI::FANN    PREFIX = accessor_

double
accessor_cascade_output_change_fraction(self, value = NO_INIT)
    struct fann * self;
    double value
  CODE:
    if (items > 1) {
        fann_set_cascade_output_change_fraction(self, value);
    }
    RETVAL = fann_get_cascade_output_change_fraction(self);
  OUTPUT:
    RETVAL
  CLEANUP:
    _check_error(aTHX_ (struct fann_error *)self);


MODULE = AI::FANN    PACKAGE = AI::FANN    PREFIX = accessor_

double
accessor_cascade_output_stagnation_epochs(self, value = NO_INIT)
    struct fann * self;
    double value
  CODE:
    if (items > 1) {
        fann_set_cascade_output_stagnation_epochs(self, value);
    }
    RETVAL = fann_get_cascade_output_stagnation_epochs(self);
  OUTPUT:
    RETVAL
  CLEANUP:
    _check_error(aTHX_ (struct fann_error *)self);


MODULE = AI::FANN    PACKAGE = AI::FANN    PREFIX = accessor_

double
accessor_cascade_candidate_change_fraction(self, value = NO_INIT)
    struct fann * self;
    double value
  CODE:
    if (items > 1) {
        fann_set_cascade_candidate_change_fraction(self, value);
    }
    RETVAL = fann_get_cascade_candidate_change_fraction(self);
  OUTPUT:
    RETVAL
  CLEANUP:
    _check_error(aTHX_ (struct fann_error *)self);


MODULE = AI::FANN    PACKAGE = AI::FANN    PREFIX = accessor_

unsigned int
accessor_cascade_candidate_stagnation_epochs(self, value = NO_INIT)
    struct fann * self;
    unsigned int value
  CODE:
    if (items > 1) {
        fann_set_cascade_candidate_stagnation_epochs(self, value);
    }
    RETVAL = fann_get_cascade_candidate_stagnation_epochs(self);
  OUTPUT:
    RETVAL
  CLEANUP:
    _check_error(aTHX_ (struct fann_error *)self);


MODULE = AI::FANN    PACKAGE = AI::FANN    PREFIX = accessor_

fann_type
accessor_cascade_weight_multiplier(self, value = NO_INIT)
    struct fann * self;
    fann_type value
  CODE:
    if (items > 1) {
        fann_set_cascade_weight_multiplier(self, value);
    }
    RETVAL = fann_get_cascade_weight_multiplier(self);
  OUTPUT:
    RETVAL
  CLEANUP:
    _check_error(aTHX_ (struct fann_error *)self);


MODULE = AI::FANN    PACKAGE = AI::FANN    PREFIX = accessor_

fann_type
accessor_cascade_candidate_limit(self, value = NO_INIT)
    struct fann * self;
    fann_type value
  CODE:
    if (items > 1) {
        fann_set_cascade_candidate_limit(self, value);
    }
    RETVAL = fann_get_cascade_candidate_limit(self);
  OUTPUT:
    RETVAL
  CLEANUP:
    _check_error(aTHX_ (struct fann_error *)self);


MODULE = AI::FANN    PACKAGE = AI::FANN    PREFIX = accessor_

unsigned int
accessor_cascade_max_out_epochs(self, value = NO_INIT)
    struct fann * self;
    unsigned int value
  CODE:
    if (items > 1) {
        fann_set_cascade_max_out_epochs(self, value);
    }
    RETVAL = fann_get_cascade_max_out_epochs(self);
  OUTPUT:
    RETVAL
  CLEANUP:
    _check_error(aTHX_ (struct fann_error *)self);


MODULE = AI::FANN    PACKAGE = AI::FANN    PREFIX = accessor_

unsigned int
accessor_cascade_max_cand_epochs(self, value = NO_INIT)
    struct fann * self;
    unsigned int value
  CODE:
    if (items > 1) {
        fann_set_cascade_max_cand_epochs(self, value);
    }
    RETVAL = fann_get_cascade_max_cand_epochs(self);
  OUTPUT:
    RETVAL
  CLEANUP:
    _check_error(aTHX_ (struct fann_error *)self);


MODULE = AI::FANN    PACKAGE = AI::FANN    PREFIX = accessor_

unsigned int
accessor_cascade_num_candidates(self)
	struct fann * self;
  CODE:
    RETVAL = fann_get_cascade_num_candidates(self);
  OUTPUT:
    RETVAL
  CLEANUP:
    _check_error(aTHX_ (struct fann_error *)self);


MODULE = AI::FANN    PACKAGE = AI::FANN    PREFIX = accessor_

unsigned int
accessor_cascade_num_candidate_groups(self, value = NO_INIT)
    struct fann * self;
    unsigned int value
  CODE:
    if (items > 1) {
        fann_set_cascade_num_candidate_groups(self, value);
    }
    RETVAL = fann_get_cascade_num_candidate_groups(self);
  OUTPUT:
    RETVAL
  CLEANUP:
    _check_error(aTHX_ (struct fann_error *)self);


MODULE = AI::FANN    PACKAGE = AI::FANN    PREFIX = accessor_

enum fann_activationfunc_enum
accessor_neuron_activation_function(self, layer, neuron_index, value = NO_INIT)

genaccessors  view on Meta::CPAN

rprop_decrease_factor, double, fann_get_rprop_decrease_factor, fann_set_rprop_decrease_factor
rprop_delta_min, double, fann_get_rprop_delta_min, fann_set_rprop_delta_min
rprop_delta_max, double, fann_get_rprop_delta_max, fann_set_rprop_delta_max
num_inputs, unsigned int, fann_get_num_input
num_outputs, unsigned int, fann_get_num_output
total_neurons, unsigned int, fann_get_total_neurons
total_connections, unsigned int, fann_get_total_connections
connection_rate, double, fann_get_connection_rate
MSE, double, fann_get_MSE
bit_fail, unsigned int, fann_get_bit_fail
cascade_output_change_fraction, double, fann_get_cascade_output_change_fraction, fann_set_cascade_output_change_fraction
cascade_output_stagnation_epochs, double, fann_get_cascade_output_stagnation_epochs, fann_set_cascade_output_stagnation_epochs
cascade_candidate_change_fraction, double, fann_get_cascade_candidate_change_fraction, fann_set_cascade_candidate_change_fraction
cascade_candidate_stagnation_epochs, unsigned int, fann_get_cascade_candidate_stagnation_epochs, fann_set_cascade_candidate_stagnation_epochs
cascade_weight_multiplier, fann_type, fann_get_cascade_weight_multiplier, fann_set_cascade_weight_multiplier
cascade_candidate_limit, fann_type, fann_get_cascade_candidate_limit, fann_set_cascade_candidate_limit
cascade_max_out_epochs, unsigned int, fann_get_cascade_max_out_epochs, fann_set_cascade_max_out_epochs
cascade_max_cand_epochs, unsigned int, fann_get_cascade_max_cand_epochs, fann_set_cascade_max_cand_epochs
cascade_num_candidates, unsigned int, fann_get_cascade_num_candidates
cascade_num_candidate_groups, unsigned int, fann_get_cascade_num_candidate_groups, fann_set_cascade_num_candidate_groups
neuron_activation_function, enum fann_activationfunc_enum, fann_get_activation_function, fann_set_activation_function, value, layer, neuron_index
layer_activation_function, enum fann_activationfunc_enum, , fann_set_activation_function_layer, value, layer
hidden_activation_function, enum fann_activationfunc_enum, , fann_set_activation_function_hidden
output_activation_function, enum fann_activationfunc_enum, , fann_set_activation_function_output
neuron_activation_steepness, fann_type, fann_get_activation_steepness, fann_set_activation_steepness, value, layer, neuron
layer_activation_steepness, fann_type, , fann_set_activation_steepness_layer, value, layer
hidden_activation_steepness, fann_type, , fann_set_activation_steepness_hidden
output_activation_steepness, fann_type, , fann_set_activation_steepness_output
layer_num_neurons, unsigned int, fann_get_num_neurons, , layer
num_layers, unsigned int, fann_get_num_layers

lib/AI/FANN.pm  view on Meta::CPAN

-

=item $ann->train_on_file($filename, $max_epochs, $epochs_between_reports, $desired_error)

-

=item $ann->train_on_data($train_data, $max_epochs, $epochs_between_reports, $desired_error)

C<$train_data> is a AI::FANN::TrainData object.

=item $ann->cascadetrain_on_file($filename, $max_neurons, $neurons_between_reports, $desired_error)

-

=item $ann->cascadetrain_on_data($train_data, $max_neurons, $neurons_between_reports, $desired_error)

C<$train_data> is a AI::FANN::TrainData object.

=item $ann->train_epoch($train_data)

C<$train_data> is a AI::FANN::TrainData object.

=item $ann->print_connections

-

=item $ann->print_parameters

-

=item $ann->cascade_activation_functions()

returns a list of the activation functions used for cascade training.

=item $ann->cascade_activation_functions(@activation_functions)

sets the list of activation function to use for cascade training.

=item $ann->cascade_activation_steepnesses()

returns a list of the activation steepnesses used for cascade training.

=item $ann->cascade_activation_steepnesses(@activation_steepnesses)

sets the list of activation steepnesses to use for cascade training.

=item $ann->training_algorithm

=item $ann->training_algorithm($training_algorithm)

-

=item $ann->train_error_function

=item $ann->train_error_function($error_function)

lib/AI/FANN.pm  view on Meta::CPAN

-

=item $ann->MSE

-

=item $ann->bit_fail

-

=item cascade_output_change_fraction

=item cascade_output_change_fraction($fraction)

-

=item $ann->cascade_output_stagnation_epochs

=item $ann->cascade_output_stagnation_epochs($epochs)

-

=item $ann->cascade_candidate_change_fraction

=item $ann->cascade_candidate_change_fraction($fraction)

-

=item $ann->cascade_candidate_stagnation_epochs

=item $ann->cascade_candidate_stagnation_epochs($epochs)

-

=item $ann->cascade_weight_multiplier

=item $ann->cascade_weight_multiplier($multiplier)

-

=item $ann->cascade_candidate_limit

=item $ann->cascade_candidate_limit($limit)

-

=item $ann->cascade_max_out_epochs

=item $ann->cascade_max_out_epochs($epochs)

-

=item $ann->cascade_max_cand_epochs

=item $ann->cascade_max_cand_epochs($epochs)

-

=item $ann->cascade_num_candidates

-

=item $ann->cascade_num_candidate_groups

=item $ann->cascade_num_candidate_groups($groups)

-

=item $ann->neuron_activation_function($layer_index, $neuron_index)

=item $ann->neuron_activation_function($layer_index, $neuron_index, $activation_function)

-

=item $ann->layer_activation_function($layer_index, $activation_function)