Describe a neural network : Evaluate Accuracy

The video tutorial explains confusion matrices and various accuracy measures in classification problems, focusing on binary classification. It covers true positives, true negatives, false positives, and false negatives, and how these contribute to overall accuracy. The tutorial also discusses precision and recall, emphasizing their importance in diagnosing diseases. Additionally, it introduces Cohen's Kappa and predictive values, highlighting their roles in evaluating classifier performance.

Describe how precision is calculated and its importance in classification.

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What does Cohen's Kappa measure and why is it relevant in classification tasks?

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