How to use do machine learning/neural networks in matlab?

I have a Displacement Trend, lets say

D=[0 1 2 3 4]

Associated with this Power Used:

P=[0 5 4 2]

The data recorded of the output value is:

Force=[0 4 3 2] This is the target output to train the model

My problem is how can i define the train matrix and target matrix if i did this test multiple times, so i have:

D1,P1 that produce F1

D2,P2 that procuce F2

D3,P3 that produce F3

and so on..

and also what you suggest doing for doing this kind of analysis. Which model/app could i use

Thank you in advance.

Answer 1

[Sai Pavan]

Hi Davide,

I understand that you want to know how to organize data and perform regression analysis to estimate force using neural networks and other machine learning models.

The workflow to define the training and target matrices for your data and to perform regression analysis to model the input-output relationship in MATLAB is as follows:

• Organize the input data (displacement and power) into a matrix format. Each row represents a different test instance, and each column represents a different input variable (displacement and power). This matrix will be used as the input for training your regression model.
• Organize the target output data (force) into a vector. If there are multiple test instances, we can have a vector of target outputs corresponding to each test.
• Here is a code snippet that demonstrates how we can organize the data:

D = [0 1 2 3 4];  % Displacement
P = [0 5 4 2 1];  % Power
Force = [0 4 3 2 1];  % Target output

inputData = [D; P]';  % Each row represents a test instance, columns represent input variables
targetData = Force;  % Vector of target outputs

• Once we have organized the data, we can use regression techniques such as linear regression, polynomial regression, support vector machines (SVM), decision trees, neural networks and more in the Regression Learner app, available in the Statistics and Machine Learning Toolbox, to interactively explore and compare different regression models for the data.
• Here is code snippet that illustrates how one can perform linear regression using the “fitlm” function in MATLAB:

lm = fitlm(inputData, targetData);  % Fit a linear regression model
disp(lm); % Display the regression results

• If you need more advanced customization with the neural network architecture and loss functions, one can directly work with the Neural Network Toolbox and use MATLAB's programming interface to define and train neural network models for regression.

Please refer to the below documentation:

• To learn how to use Regression Learner app: https://www.mathworks.com/help/stats/regressionlearner-app.html
• To learn how to model and train a neural network with Neural Network Toolbox: https://www.mathworks.com/help/deeplearning/ref/feedforwardnet.html

Hope it helps.

Regards,

Sai Pavan