fann_subset_train_data
(PECL fann >= 1.0.0)
fann_subset_train_data — Returns an copy of a subset of the train data
Description
resource fann_subset_train_data
( resource
$data
, int $pos
, int $length
)Returns an copy of a subset of the train data resource, starting at position pos and length elements forward.
The fann_subset_train_data(train_data, 0, fann_length_train_data(train_data)) do the same as fann_duplicate_train_data()
Parameters
-
data
-
Neural network training data resource.
-
pos
-
Starting position.
-
length
-
The number of copied elements.
Return Values
Returns a train data resource on success, or FALSE
on error.
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- Другие базовые расширения
- FANN (Fast Artificial Neural Network)
- fann_cascadetrain_on_data
- fann_cascadetrain_on_file
- fann_clear_scaling_params
- fann_copy
- fann_create_from_file
- fann_create_shortcut_array
- fann_create_shortcut
- fann_create_sparse_array
- fann_create_sparse
- fann_create_standard_array
- fann_create_standard
- fann_create_train_from_callback
- fann_create_train
- fann_descale_input
- fann_descale_output
- fann_descale_train
- fann_destroy_train
- fann_destroy
- fann_duplicate_train_data
- fann_get_activation_function
- fann_get_activation_steepness
- fann_get_bias_array
- fann_get_bit_fail_limit
- fann_get_bit_fail
- fann_get_cascade_activation_functions_count
- fann_get_cascade_activation_functions
- fann_get_cascade_activation_steepnesses_count
- fann_get_cascade_activation_steepnesses
- fann_get_cascade_candidate_change_fraction
- fann_get_cascade_candidate_limit
- fann_get_cascade_candidate_stagnation_epochs
- fann_get_cascade_max_cand_epochs
- fann_get_cascade_max_out_epochs
- fann_get_cascade_min_cand_epochs
- fann_get_cascade_min_out_epochs
- fann_get_cascade_num_candidate_groups
- fann_get_cascade_num_candidates
- fann_get_cascade_output_change_fraction
- fann_get_cascade_output_stagnation_epochs
- fann_get_cascade_weight_multiplier
- fann_get_connection_array
- fann_get_connection_rate
- fann_get_errno
- fann_get_errstr
- fann_get_layer_array
- fann_get_learning_momentum
- fann_get_learning_rate
- fann_get_MSE
- fann_get_network_type
- fann_get_num_input
- fann_get_num_layers
- fann_get_num_output
- fann_get_quickprop_decay
- fann_get_quickprop_mu
- fann_get_rprop_decrease_factor
- fann_get_rprop_delta_max
- fann_get_rprop_delta_min
- fann_get_rprop_delta_zero
- fann_get_rprop_increase_factor
- fann_get_sarprop_step_error_shift
- fann_get_sarprop_step_error_threshold_factor
- fann_get_sarprop_temperature
- fann_get_sarprop_weight_decay_shift
- fann_get_total_connections
- fann_get_total_neurons
- fann_get_train_error_function
- fann_get_train_stop_function
- fann_get_training_algorithm
- fann_init_weights
- fann_length_train_data
- fann_merge_train_data
- fann_num_input_train_data
- fann_num_output_train_data
- fann_print_error
- fann_randomize_weights
- fann_read_train_from_file
- fann_reset_errno
- fann_reset_errstr
- fann_reset_MSE
- fann_run
- fann_save_train
- fann_save
- fann_scale_input_train_data
- fann_scale_input
- fann_scale_output_train_data
- fann_scale_output
- fann_scale_train_data
- fann_scale_train
- fann_set_activation_function_hidden
- fann_set_activation_function_layer
- fann_set_activation_function_output
- fann_set_activation_function
- fann_set_activation_steepness_hidden
- fann_set_activation_steepness_layer
- fann_set_activation_steepness_output
- fann_set_activation_steepness
- fann_set_bit_fail_limit
- fann_set_callback
- fann_set_cascade_activation_functions
- fann_set_cascade_activation_steepnesses
- fann_set_cascade_candidate_change_fraction
- fann_set_cascade_candidate_limit
- fann_set_cascade_candidate_stagnation_epochs
- fann_set_cascade_max_cand_epochs
- fann_set_cascade_max_out_epochs
- fann_set_cascade_min_cand_epochs
- fann_set_cascade_min_out_epochs
- fann_set_cascade_num_candidate_groups
- fann_set_cascade_output_change_fraction
- fann_set_cascade_output_stagnation_epochs
- fann_set_cascade_weight_multiplier
- fann_set_error_log
- fann_set_input_scaling_params
- fann_set_learning_momentum
- fann_set_learning_rate
- fann_set_output_scaling_params
- fann_set_quickprop_decay
- fann_set_quickprop_mu
- fann_set_rprop_decrease_factor
- fann_set_rprop_delta_max
- fann_set_rprop_delta_min
- fann_set_rprop_delta_zero
- fann_set_rprop_increase_factor
- fann_set_sarprop_step_error_shift
- fann_set_sarprop_step_error_threshold_factor
- fann_set_sarprop_temperature
- fann_set_sarprop_weight_decay_shift
- fann_set_scaling_params
- fann_set_train_error_function
- fann_set_train_stop_function
- fann_set_training_algorithm
- fann_set_weight_array
- fann_set_weight
- fann_shuffle_train_data
- fann_subset_train_data
- fann_test_data
- fann_test
- fann_train_epoch
- fann_train_on_data
- fann_train_on_file
- fann_train
Коментарии
<?php
// Use this code to split your data into smaller sets.
// Useful for splitting your training data into training and testing groups
// Load Data
$data_file = "MyTrainingData.data";
$train_data = fann_read_train_from_file(dirname(__FILE__) . DIRECTORY_SEPARATOR . $data_file);
// Calculate how many examples are in the first group
$total_length = fann_length_train_data($train_data);
$a_length = floor($total_length / 10);
// Split the subsets
$training_data_a = fann_subset_train_data($train_data, 0, $a_length);
$training_data_b = fann_subset_train_data($train_data, $a_length, $total_length-$a_length);
// Save the training data to separate files
fann_save_train ($training_data_a, 'MyTrainingData_Subset_A.data'); // 1/10 of the training data
fann_save_train ($training_data_b, 'MyTrainingData_Subset_B.data'); // 9/10 of the training data