Here is a list of all functions with links to the classes they belong to:
- s -
- samples_from_JSON() : opennn::Dataset
- samples_to_JSON() : opennn::Dataset
- save() : opennn::Dataset, opennn::Descriptives, opennn::Histogram, opennn::InputsSelection, opennn::JsonDocument, opennn::ModelExpression, opennn::ModelSelection, opennn::NeuralNetwork, opennn::NeuronSelection, opennn::opennn::JsonDocument, opennn::Optimizer, opennn::TestingAnalysis::GoodnessOfFitAnalysis, opennn::TestingAnalysis, opennn::TrainingResults, opennn::TrainingStrategy
- save_confusion() : opennn::TestingAnalysis
- save_data() : opennn::Dataset
- save_data_binary() : opennn::Dataset
- save_misclassified_samples() : opennn::TestingAnalysis
- save_misclassified_samples_statistics() : opennn::TestingAnalysis
- save_multiple_classification_tests() : opennn::TestingAnalysis
- save_outputs() : opennn::NeuralNetwork
- save_parameters() : opennn::NeuralNetwork
- save_well_classified_samples() : opennn::TestingAnalysis
- save_well_classified_samples_statistics() : opennn::TestingAnalysis
- scale_data() : opennn::Dataset
- scale_features() : opennn::Dataset, opennn::ImageDataset
- Scaling() : opennn::Scaling
- ScopedTimer() : opennn::profiler::ScopedTimer
- scrub_missing_values() : opennn::Dataset
- set() : opennn::Addition, opennn::Attention, opennn::BackPropagation, opennn::BackPropagationLM, opennn::Batch, opennn::BatchNorm, opennn::Bound, opennn::Bounding, opennn::BoxPlot, opennn::Combination, opennn::Configuration, opennn::Convolution, opennn::Convolutional, opennn::ConvolutionalRelu, opennn::Dataset, opennn::Dense, opennn::DenseRelu, opennn::Descriptives, opennn::Embedding, opennn::EmbeddingLookup, opennn::Flatten, opennn::ForwardPropagation, opennn::InputsSelection, opennn::InputsSelectionResults, opennn::Json, opennn::LayerNorm, opennn::Loss, opennn::ModelSelection, opennn::MultiHeadAttention, opennn::MultiHeadProjection, opennn::NeuronSelection, opennn::Normalization3d, opennn::opennn::Configuration, opennn::opennn::ForwardPropagation, opennn::opennn::Json, opennn::Optimizer, opennn::OptimizerData, opennn::Pool, opennn::Pooling3d, opennn::Pooling, opennn::Recurrent, opennn::ResponseOptimization::Domain, opennn::ResponseOptimization, opennn::Scale, opennn::Scaling, opennn::TestingAnalysis::GoodnessOfFitAnalysis, opennn::TrainingStrategy, opennn::Transformer, opennn::Unscale, opennn::Unscaling, opennn::Variable, opennn::VGG16
- set_activation_function() : opennn::Convolutional, opennn::Dense, opennn::Recurrent
- set_add_positional_encoding() : opennn::Embedding
- set_augmentation() : opennn::ImageDataset
- set_batch_normalization() : opennn::Convolutional, opennn::Dense
- set_batch_size() : opennn::AdaptiveMomentEstimation, opennn::StochasticGradientDescent, opennn::TestingAnalysis
- set_beta_1() : opennn::AdaptiveMomentEstimation
- set_beta_2() : opennn::AdaptiveMomentEstimation
- set_binary_variables() : opennn::Dataset
- set_bounding_method() : opennn::Bounding
- set_categories() : opennn::Variable
- set_centers_random() : opennn::KMeans
- set_cluster_number() : opennn::KMeans
- set_codification() : opennn::Dataset
- set_column_stride() : opennn::Convolutional, opennn::ConvolutionalRelu, opennn::Pooling
- set_compute_dtype() : opennn::Layer
- set_condition() : opennn::ResponseOptimization
- set_convolution_type() : opennn::Convolutional, opennn::ConvolutionalRelu
- set_damping_parameter() : opennn::LevenbergMarquardtAlgorithm
- set_damping_parameter_factor() : opennn::LevenbergMarquardtAlgorithm
- set_data() : opennn::Dataset
- set_data_binary_classification() : opennn::Dataset
- set_data_constant() : opennn::Dataset
- set_data_integer() : opennn::Dataset
- set_data_path() : opennn::Dataset
- set_data_random() : opennn::Dataset, opennn::ImageDataset
- set_data_rosenbrock() : opennn::Dataset
- set_dataset() : opennn::Loss, opennn::TestingAnalysis, opennn::TrainingStrategy
- set_default() : opennn::AdaptiveMomentEstimation, opennn::Dataset, opennn::GeneticAlgorithm, opennn::GrowingInputs, opennn::GrowingNeurons, opennn::LevenbergMarquardtAlgorithm, opennn::ModelSelection, opennn::NeuralNetwork, opennn::NeuronSelection, opennn::QuasiNewtonMethod, opennn::StochasticGradientDescent, opennn::TrainingStrategy
- set_default_variable_names() : opennn::Dataset
- set_default_variable_roles() : opennn::Dataset
- set_default_variable_roles_forecasting() : opennn::Dataset
- set_default_variable_scalers() : opennn::Dataset
- set_descriptives() : opennn::Scaling, opennn::Unscaling
- set_display() : opennn::Dataset, opennn::InputsSelection, opennn::NeuronSelection, opennn::Optimizer
- set_display_period() : opennn::Optimizer
- set_dropout_rate() : opennn::Attention, opennn::Dense, opennn::Embedding, opennn::MultiHeadAttention, opennn::Transformer
- set_elitism_size() : opennn::GeneticAlgorithm
- set_error() : opennn::Loss
- set_evaluations_number() : opennn::ResponseOptimization
- set_feature_names() : opennn::Dataset
- set_function() : opennn::Activation
- set_future_time_steps() : opennn::TimeSeriesDataset
- set_gmt() : opennn::Dataset
- set_has_header() : opennn::Dataset
- set_has_ids() : opennn::Dataset
- set_image_padding() : opennn::ImageDataset
- set_individuals_number() : opennn::GeneticAlgorithm
- set_initial_decay() : opennn::StochasticGradientDescent
- set_initial_learning_rate() : opennn::StochasticGradientDescent
- set_initialization_method() : opennn::GeneticAlgorithm
- set_input_names() : opennn::NeuralNetwork
- set_input_shape() : opennn::Addition, opennn::Bounding, opennn::Convolutional, opennn::ConvolutionalRelu, opennn::Dense, opennn::DenseRelu, opennn::Flatten, opennn::Layer, opennn::MultiHeadAttention, opennn::NeuralNetwork, opennn::Normalization3d, opennn::Pooling3d, opennn::Pooling, opennn::Recurrent, opennn::Scaling, opennn::Unscaling
- set_input_variables() : opennn::NeuralNetwork
- set_input_variables_unused() : opennn::Dataset
- set_input_vocabulary() : opennn::LanguageDataset, opennn::Transformer
- set_iterations() : opennn::ResponseOptimization
- set_label() : opennn::Layer
- set_layer_input_indices() : opennn::NeuralNetwork
- set_layers_number() : opennn::NeuralNetwork
- set_learning_rate() : opennn::AdaptiveMomentEstimation
- set_loss() : opennn::Optimizer, opennn::TrainingStrategy
- set_loss_goal() : opennn::Optimizer
- set_lower_bound() : opennn::Bounding
- set_lower_bounds() : opennn::Bounding
- set_maximum_correlation() : opennn::GrowingInputs
- set_maximum_damping_parameter() : opennn::LevenbergMarquardtAlgorithm
- set_maximum_epochs() : opennn::InputsSelection, opennn::NeuronSelection, opennn::Optimizer
- set_maximum_inputs_number() : opennn::GeneticAlgorithm, opennn::GrowingInputs
- set_maximum_neurons() : opennn::NeuronSelection
- set_maximum_time() : opennn::InputsSelection, opennn::NeuronSelection, opennn::Optimizer
- set_maximum_validation_failures() : opennn::InputsSelection, opennn::NeuronSelection, opennn::Optimizer
- set_min_max_range() : opennn::Scaling, opennn::Unscaling
- set_minimum_correlation() : opennn::GrowingInputs
- set_minimum_damping_parameter() : opennn::LevenbergMarquardtAlgorithm
- set_minimum_inputs_number() : opennn::GeneticAlgorithm, opennn::GrowingInputs
- set_minimum_loss_decrease() : opennn::LevenbergMarquardtAlgorithm, opennn::QuasiNewtonMethod
- set_minimum_neurons() : opennn::NeuronSelection
- set_missing_values_label() : opennn::Dataset
- set_missing_values_method() : opennn::Dataset
- set_momentum() : opennn::Dense, opennn::StochasticGradientDescent
- set_multi_target() : opennn::TimeSeriesDataset
- set_mutation_rate() : opennn::GeneticAlgorithm
- set_names() : opennn::Optimizer
- set_nesterov() : opennn::StochasticGradientDescent
- set_neural_network() : opennn::Loss, opennn::TestingAnalysis, opennn::TrainingStrategy
- set_neurons_increment() : opennn::GrowingNeurons
- set_normalization_coefficient() : opennn::Loss
- set_optimization_algorithm() : opennn::TrainingStrategy
- set_output_names() : opennn::NeuralNetwork
- set_output_shape() : opennn::Bounding, opennn::Dense, opennn::DenseRelu, opennn::Layer, opennn::Recurrent, opennn::Scaling, opennn::Unscaling
- set_output_variables() : opennn::NeuralNetwork
- set_output_vocabulary() : opennn::Transformer
- set_padding_height() : opennn::Pooling
- set_padding_width() : opennn::Pooling
- set_parameters() : opennn::NeuralNetwork
- set_parameters_glorot() : opennn::BatchNorm, opennn::Combination, opennn::Convolution, opennn::EmbeddingLookup, opennn::LayerNorm, opennn::MultiHeadProjection, opennn::NeuralNetwork, opennn::Operator
- set_parameters_random() : opennn::BatchNorm, opennn::Combination, opennn::Convolution, opennn::EmbeddingLookup, opennn::LayerNorm, opennn::MultiHeadProjection, opennn::NeuralNetwork, opennn::Operator
- set_past_time_steps() : opennn::TimeSeriesDataset
- set_perfect() : opennn::Correlation
- set_pool_size() : opennn::Pooling
- set_pooling_method() : opennn::Pooling3d, opennn::Pooling
- set_rate() : opennn::Dropout
- set_regularization() : opennn::Loss
- set_regularization_weight() : opennn::Loss
- set_relative_tolerance() : opennn::ResponseOptimization
- set_role() : opennn::Variable
- set_row_stride() : opennn::Convolutional, opennn::ConvolutionalRelu, opennn::Pooling
- set_sample_role() : opennn::Dataset
- set_sample_roles() : opennn::Dataset
- set_scale_embedding() : opennn::Embedding
- set_scaler() : opennn::Variable
- set_scalers() : opennn::Scaling, opennn::Unscaling
- set_scaling() : opennn::Optimizer
- set_separator() : opennn::Dataset
- set_separator_name() : opennn::Dataset
- set_separator_string() : opennn::Dataset
- set_shape() : opennn::Dataset
- set_target_vocabulary() : opennn::LanguageDataset
- set_threads_number() : opennn::Backend, opennn::opennn::Backend
- set_time_variable_index() : opennn::TimeSeriesDataset
- set_training_strategy() : opennn::NeuronSelection
- set_trials_number() : opennn::InputsSelection, opennn::NeuronSelection
- set_type() : opennn::Variable
- set_unscaling() : opennn::Optimizer
- set_upper_bound() : opennn::Bounding
- set_upper_bounds() : opennn::Bounding
- set_validation_error_goal() : opennn::InputsSelection, opennn::NeuronSelection
- set_variable_indices() : opennn::Dataset
- set_variable_names() : opennn::Dataset
- set_variable_role() : opennn::Dataset
- set_variable_roles() : opennn::Dataset
- set_variable_scalers() : opennn::Dataset
- set_variable_type() : opennn::Dataset
- set_variable_types() : opennn::Dataset
- set_variables() : opennn::Dataset
- set_variables_number() : opennn::Dataset
- set_zoom_factor() : opennn::ResponseOptimization
- setup_device_training() : opennn::Optimizer
- setZero() : opennn::Buffer, opennn::opennn::Buffer
- Shape() : opennn::opennn::Shape, opennn::Shape
- should_display() : opennn::Optimizer
- SimpleResNet() : opennn::SimpleResNet
- size() : opennn::opennn::Shape, opennn::opennn::TensorView, opennn::Shape, opennn::TensorView
- size_in_floats() : opennn::Buffer, opennn::opennn::Buffer
- split_samples() : opennn::Dataset
- split_samples_random() : opennn::Dataset
- split_samples_sequential() : opennn::Dataset
- state_specs() : opennn::BatchNorm, opennn::Bound, opennn::EmbeddingLookup, opennn::Operator, opennn::Scale, opennn::Unscale
- StochasticGradientDescent() : opennn::StochasticGradientDescent
- string_to_regularization() : opennn::Loss
- swap() : opennn::Buffer, opennn::opennn::Buffer
- sync_device() : opennn::Optimizer