SAIF AKHTAR
clc
load mnist_reduced.mat;
X = im2single(MnistReducedX);
Y = im2single(MnistReducedY);
X_train = 255*X(1:980, :) ;
Y_train = 255*Y(1:980) ;
X_test = 255*X(981:1000, :) ;
Y_test = 255*Y(981:1000) ;
yfit = trainedModel.predictFcn(X_test) %Exported Model
Y_test_transpose = transpose(Y_test)
(2 incorrect / 20 total)*100 = 10% error
The 3 best models:
0