how to create a neural network in matlab in matlab

Here's an example code to create a neural network in Matlab:

main.m
% Import your dataset
data = readtable('myData.csv');

% Define your training and testing sets
trainData = data(1:800,:); 
testData = data(801:end,:);

% Define the architecture of the neural network
net = feedforwardnet([10 5]);

% Train the neural network using the training data
net = train(net, trainData{:, 1:end-1}', trainData{:,end}');

% Evaluate the trained neural network using the testing data
predicted = net(testData{:, 1:end-1}');

% Calculate the accuracy of the neural network
accuracy = sum(round(predicted') == testData{:,end}) / length(predicted);
567 chars
19 lines

In this example, we first import the dataset that we want to use for training and testing. We then split the data into two sets, one for training and one for testing.

We define the architecture of the neural network by creating a new feedforward neural network with 2 hidden layers containing 10 and 5 neurons, respectively.

We use the training set to train the neural network using the train function.

Finally, we use the testing set to evaluate the performance of the trained neural network. The predicted variable contains the predicted values of the network, and we can calculate the accuracy of the neural network by comparing the predicted values with the actual values.