Approach to interpret the following confusion matrix

Question

I know that from the confusion matrix, we can figure out how good a classifier is in terms of guessing what is right and wrong.

In the case below, I have sample of the following data:

After running the Random Tree classifier, I get the following results.

Does that mean that out of the build wind float, the classifier was only able to get 53/70 correct?

Or in the case of the build wind non float, the classifier was only able to get 53/76 correct?

Just need some clarity - thanks.

Answer 1

Yes it does. While the columns represent "classified as", the rows indicate the true label.

So for build wind float the confusion matrix can be read as:

From all the samples we have labeled with class a:

• 53 were classified as a (true positives here)
• 11 were classified a b
• 6 were classified as c
• ...

So you find the correct guesses at the diagonal of the matrix and the for the rest you can see which classes were assigned instead.