MATLAB: How to predict each pixel of image using regression model

image processingImage Processing ToolboxregressionStatistics and Machine Learning Toolbox

I have the following code that loops over each pixel of a .tif image to predict responses using ensemble of regression models.
X is a 753*6 numeric array which has 6 variables (also columns), and 753 rows. NR = 1380, NC = 1464.
I understand the error's meaning (The dimensions on both sides do not match each other), but I really do not know how to fix it. I imagine the result I need should be a 1380*1464 numeric array.
a = imread('LE71250521999276_b1.tif')
[NR,NC] = size(a);
Yfit = zeros(NR,NC);
for i = 1:NR
      for j = 1:NC
          Yfit(i,j) = predict(Mdl1999276,X);
      end
  end
ERROR: Assignment has more non-singleton rhs dimensions than non-singleton subscripts
Thank you for helping!!

Best Answer

Why are you using all of X to do the prediction each time?
Why are you reading in the image if you are not going to predict based on its values?
Ensembles often make one prediction per ensemble member per sample; if so then you might need to analyze a vector of results to decide what one output you want.
Predictions sometimes output a probability per class rather than a single class number.
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