colormapconfusion matriximagescStatistics and Machine Learning Toolbox
A = [1195 3 54; 0 631 34; 90 135 158]; close all, clear all, clc [ x t ] = cancer_dataset;[ I N ] = size(x) %[ 9 699 ]
[ O N ] = size(t) %[ 2 699 ]
vart = mean(var(t',1)) % 0.2259
t1 = t(1,:); t2 = t(2,:);N1 = sum(t1), N2 = sum(t2) % 458, 241
m1 = mean(t1), m2 = mean(t2) % 0.6552, 0.3448
vart1 = var(t1,1), vart2 = var(t2,1)% 0.2259, 0.2259
net = patternnet(10);rng(0) [net tr y e ] = train(net,x,t);% y = net(x); e = t - y;
NMSE = mse(e)/vart % 0.0984
% NOTE: Although regression error ~ 10%)
% classifcation error will only be ~ 3%
[c,cm,ind,per] = confusion(t,y)% cm = 446 12 ( 12/458 = 0.0262 )
% 8 233 ( 8/241 = 0.0332 )
% c = 0.0286 ( 20/699 = 0.0286 )
% ( 8/454 = 0.0176 , 12/245 = 0.0490 )
% per = 0.0490 0.0176 0.9824 0.9510
% 0.0176 0.0490 0.9510 0.9824
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
clear; % Erase all existing variables. Or clearvars if you want.
workspace; % Make sure the workspace panel is showing.
format long g;format compact;fontSize = 15;%===============================================================================
% Get the name of the image the user wants to use.
baseFileName = 'originalimage.jpg';% Get the full filename, with path prepended.
folder = pwdfullFileName = fullfile(folder, baseFileName);% Check if file exists.
if ~exist(fullFileName, 'file') % The file doesn't exist -- didn't find it there in that folder.
% Check the entire search path (other folders) for the file by stripping off the folder.
fullFileNameOnSearchPath = baseFileName; % No path this time.
if ~exist(fullFileNameOnSearchPath, 'file') % Still didn't find it. Alert user.
errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName); uiwait(warndlg(errorMessage)); return; endend%===============================================================================% Read in demo image.
rgbImage = imread(fullFileName);% Get the dimensions of the image.
[imageRows, imageColumns, numberOfColorChannels] = size(rgbImage);% Display the original image.
subplot(3, 3, 1);imshow(rgbImage, []);axis on;caption = sprintf('Original Color Image, %s', baseFileName);title(caption, 'FontSize', fontSize, 'Interpreter', 'None');% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0 1 1]);% Get rid of tool bar and pulldown menus that are along top of figure.
set(gcf, 'Toolbar', 'none', 'Menu', 'none');% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')drawnow;hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Crop the image
rgbImage = rgbImage(29:391, 87:762, :);% Convert to HSV color space so we can segment the saturation channel.
hsvImage = rgb2hsv(rgbImage);sImage = hsvImage(:, :, 2);% Display the image.
subplot(3, 3, 2);imshow(sImage, []);axis on;caption = sprintf('Saturation Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;% Display the histogram
subplot(3, 3, 3);histogram(sImage);grid on;title('Histogram of Saturation Image', 'FontSize', fontSize);% Threshold the image
saturationThreshold = 0.15;mask = sImage > saturationThreshold;% Fill holes.
mask = imfill(mask, 'holes');% Extract the two largest blobs only.
mask = bwareafilt(mask, 2);% Put a red line at the threshold.
line([saturationThreshold, saturationThreshold], ylim, 'Color', 'r', 'LineWidth', 3);% Display the image.subplot(3, 3, 4);imshow(mask, []);axis on;caption = sprintf('Mask Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;% Give each blob an ID number.
labeledImage = bwlabel(mask);% Get the top and bottom mask
topMask = ismember(labeledImage, 1);bottomMask = ismember(labeledImage, 2);% Display the image.subplot(3, 3, 5);imshow(topMask, []);axis on;caption = sprintf('Top Mask Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;% Display the image.subplot(3, 3, 6);imshow(bottomMask, []);axis on;caption = sprintf('Bottom Mask Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;% Mask the original RGB image and display.
% Mask the image using bsxfun() function
topMaskedRgbImage = bsxfun(@times, rgbImage, cast(topMask, 'like', rgbImage));bottomMaskedRgbImage = bsxfun(@times, rgbImage, cast(bottomMask, 'like', rgbImage));% Display the image.subplot(3, 3, 7);imshow(topMaskedRgbImage, []);axis on;caption = sprintf('Top Mask Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;% Display the image.subplot(3, 3, 8);imshow(bottomMaskedRgbImage, []);axis on;caption = sprintf('Bottom Mask Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;
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