Function Approximation and Nonlinear Regression

Create a neural network to generalize nonlinear relationships between example inputs and outputs

App

Risolve il problema del fitting utilizzando reti feed-forward a due livelli

`nftool`	Apre l’app Neural Net Fitting
`view`	Visualizzazione della rete neurale superficiale

`fitnet`	Rete neurale di fitting della funzione
`feedforwardnet`	Genera una rete neurale feed-forward
`cascadeforwardnet`	Generare una rete neurale cascade-forward

`train`	Addestra una rete neurale superficiale
`trainlm`	Retropropagazione di Levenberg-Marquardt
`trainbr`	Bayesian regularization backpropagation
`trainscg`	Scaled conjugate gradient backpropagation
`trainrp`	Resilient backpropagation
`mse`	Funzione di performance dell’errore quadratico medio normalizzato
`regression`	Eseguire la regressione lineare degli output di una rete superficiale sui target (non consigliato)
`ploterrhist`	Plot error histogram
`plotfit`	Traccia il fitting della funzione
`plotperform`	Traccia la performance della rete
`plotregression`	Traccia la regressione lineare
`plottrainstate`	Traccia i valori dello stato di addestramento
`genFunction`	Generate MATLAB function for simulating shallow neural network

Reti superficiali per pattern recognition, clustering e serie temporali
Utilizza app e funzioni per progettare reti neurali superficiali per function fitting, pattern recognition, clustering e analisi di serie temporali.
Data fitting con un rete neurale superficiale
Addestra una rete neurale superficiale al fitting di un set di dati.
Create, Configure, and Initialize Multilayer Shallow Neural Networks
Prepare a multilayer shallow neural network.
Body Fat Estimation
This example illustrates how a function fitting neural network can estimate body fat percentage based on anatomical measurements.
Train and Apply Multilayer Shallow Neural Networks
Train and use a multilayer shallow network for function approximation or pattern recognition.
Analyze Shallow Neural Network Performance After Training
Analyze network performance and adjust training process, network architecture, or data.
Deploy Shallow Neural Network Functions
Simulate and deploy trained shallow neural networks using MATLAB^® tools.
Deploy Training of Shallow Neural Networks
Learn how to deploy training of shallow neural networks.

Shallow Neural Networks with Parallel and GPU Computing
Use parallel and distributed computing to speed up neural network training and simulation and handle large data.
Automatically Save Checkpoints During Neural Network Training
Save intermediate results to protect the value of long training runs.
Optimize Neural Network Training Speed and Memory
Make neural network training more efficient.
Addestramento di reti superficiali su CPU e GPU
Velocizza l’addestramento e la simulazione per grandi problemi utilizzando le reti superficiali.

Choose Neural Network Input-Output Processing Functions
Preprocess inputs and targets for more efficient training.
Configure Shallow Neural Network Inputs and Outputs
Learn how to manually configure the network before training using the configure function.
Divide Data for Optimal Neural Network Training
Use functions to divide the data into training, validation, and test sets.
Choose a Multilayer Neural Network Training Function
Comparison of training algorithms on different problem types.
Improve Shallow Neural Network Generalization and Avoid Overfitting
Learn methods to improve generalization and prevent overfitting.
Train Neural Networks with Error Weights
Learn how to use error weighting when training neural networks.
Normalize Errors of Multiple Outputs
Learn how to fit output elements with different ranges of values.

Workflow per la progettazione delle reti neurali
Apprendere le fasi principali del processo di progettazione di una rete neurale.
Four Levels of Neural Network Design
Learn the different levels of using neural network functionality.
Reti neurali superficiali multilivello e addestramento sulla retropropagazione
Workflow per la progettazione di una rete neurale superficiale multilivello feed-forward per l'adattamento di funzioni e il riconoscimento di pattern.
Multilayer Shallow Neural Network Architecture
Learn the architecture of a multilayer shallow neural network.
Understanding Shallow Network Data Structures
Learn how the format of input data structures affects the simulation of networks.
Set di dati campione per reti neurali superficiali
Elenco di set di dati campione da utilizzare negli esperimenti con reti neurali superficiali.
Neural Network Object Properties
Learn properties that define the basic features of a network.
Neural Network Subobject Properties
Learn properties that define network details such as inputs, layers, outputs, targets, biases, and weights.