I did some machine learning with some datasets. I now have accuracies and numerical numbers of prdicted classes and true classes as shown below:
The different colors (blue, orange, grey, and yellow) show different datasets. The model is pretty accurate, but has some misclassifications. For example take a look at the first row. for the Model(blue), the dataset had 3,505 responsive cells (3392+113), 3392 were correctly identified as responsive but 113 were misclassfied as resistant, making 96.776% accuracy. I want to show either all of the Model(blue) in a confusion matrix with percentages and colors (green for correct, red for incorrect) in a confusion matrix. Or maybe even all the datasets in one matrix. But I'd like to start with one forst to see how it works.
I have tried plotconfusion(), confusionmat(), but I don't think I'm inputting the data correctly.
PLEASE HELP ME.