Confusion Matrix for Machine Learning
A Confusion matrix is an N x N matrix used for evaluating the performance of a classification model, where N is the number of target classes.
The matrix compares the actual target values with those predicted by the machine learning model.
This gives us a holistic view of how well our classification model is performing and what kinds of errors it is making.
I explained the concepts of confusion matrix and its measurements for evaluation.
Also I demonstrated how to calculate confusion matrix in Python.
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The Python code is uploaded into https://github.com/AIMLModeling/Confu...