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Aster: Video: Using Confusion Matrix in Machine Learning

Genre: Statistical Analysis (Machine Learning)

Background: Learn how easy it is to leverage Aster for implementing confusion matrices. A Confusion Matrix provides a visual representation of the performance of a supervised machine learning algorithm. It makes it easy to determine if a model is confusing or mislabeling classes. We also go over some of the math involved and help to understand how confusion matrices are used in supervised machine learning.

Use Cases:
- Evaluate - Supervised Machine Learning Accuracy
- Identification of False Classifications
- Measure, Refine, and Adapt Predictive Model and Decay



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