MATLAB: Fisher's Iris data set nomogram

fisheriris_nomogram.m

%% Load data

clear
close all

load fisheriris

selection = 51:length(meas);

length = meas(selection, 1); % sepal length
width = meas(selection, 2); % sepal width
species = categorical(species(selection)); % flower species


%% Fit a model
% Store the data in a table
T = table(length, width, species);

% Fit a logistic binomial regression model
model = fitglm(T, 'Distribution', 'binomial');


%% Create a nomogram (contour plot)
% Prepare contour plot calculation, select lengths and widths to predict
lengths = min(length) : .1 : max(length);
widths = min(width) : .1 : max(width);

% Force column vectors
lengths = lengths(:);
widths = widths(:);

% Preallocate predictions
predictions = nan(numel(lengths), numel(widths));

% Predict probabilities
for j = 1:numel(widths)
    predictions(:, j) = model.predict( ...
        [lengths, widths(j) * ones(size(lengths))] ...
        );
end

% Plot the nomogram
figure
subplot 211
contour(lengths, widths, predictions', 'ShowText', 'on', 'LineColor', 'k')
grid on
title(['Nomogram of probabilities for species ''virginica'' vs. ' ...
    '''versicolor'' by sepal length and width'])
xlabel 'sepal length'
ylabel 'sepal width'
% or
subplot 212
contourf(lengths, widths, predictions', 'ShowText', 'on')
xlabel 'sepal length'
ylabel 'sepal width'