In this introduction, we give you a brief overview of what a confusion matrix is, how to create your matrix, and why you should use it. A confusion matrix, also known as an error matrix, uses a special table to help visualize the performance of your algorithm. That way, you can easily see how successful your model was when predicting the class.

Topics include true positives and negatives, target classes, and predictive models.



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