Python Artificial Intelligence Projects for Beginners

True apple
 and 
True orange
 refers to cases where the
object was actually an apple or actually an orange. The columns refer to the prediction
made by the model. We see that in our example, there are 20 apples that were predicted
correctly, while there were 5 apples that were wrongly identified as oranges.

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Building Your Own Prediction Models
Chapter 1
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Ideally, a confusion matrix should have all zeros, except for the diagonal. Here we can
calculate the accuracy by adding the figures diagonally, so that these are all the correctly
classified examples, and dividing that sum by the sum of all the numbers in the matrix:
Here we got the accuracy as 84%. To know more about confusion matrices, let's go through
another example, which involves three classes, as seen in the following diagram:
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There are three different species of iris flowers. The matrix gives raw accounts of correct
and incorrect predictions. So,