Binary Logistic Regression Curve

Hello! I am trying to create a logistical regression curve for my binary data in Figure 3. Is this possible to do in MATLAB, and if so, how could it be done? My code is below? Thanks

%Figure 2 Graphing

scatter(FactoredLength, FactoredAmplitude,5,'filled')

hold on

coefficients = polyfit(FactoredLength, FactoredAmplitude, 1);

xFit = linspace(min(FactoredLength), max(FactoredLength), 1000);

yFit = polyval(coefficients , xFit);

plot(xFit, yFit, 'r-', 'LineWidth', 2);

xlabel('Factored Length')

ylabel('Probability')

grid on;

hold off

figure

% Making data binary

Probability = ((exp(log10(FactoredAmplitude)))./(1+exp(log10(FactoredAmplitude))));

yHat(Probability > app.ThreshHoldValueEditField.Value) = 1;

yHat(Probability < app.ThreshHoldValueEditField.Value) = 0;

%Figure 3 Graphing

scatter(FactoredLength,yHat)

xlabel('Factored Length')

ylabel('Probability')

Answer 1

[Aditya Patil]

Use the fitglm function to fit logistic regression model to data. Check the following code for example,

% Create random data
x = rand(100, 1);
y = x > 0.5;
y(1:50) = x(1:50) > 0.3; % To avoid perfect seperation

% Fit model
mdl = fitglm(x, y, "Distribution", "binomial");

xnew = linspace(0,1,1000)'; % test data
ynew = predict(mdl, xnew);

scatter(x, y);
hold on;
plot(xnew, ynew);

This will give following output.