Introduction to the Confusion Matrix
A confusion matrix, also known as an error matrix, uses a special table to help visualize the performance of your classification model. That way, you can easily see how successful your model was when predicting the class. 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.
Topics include: true positives and negatives, target classes, and predictive models.
Learn more about Classification Models:
Introduction to Classification Models
Precision, Recall and F1 in Classification
One Versus One vs. One Versus All in Classification
Data Science in Minutes
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[Video] Introduction to Big Data, Data Science and Predictive Analytics
[Video] Predictive Modeling with R and Azure ML
[Blog] Azure ML Tutorial – Build a Predictive Model