Why Loss and Accuracy Metrics Conflict?
A loss function is used to optimize a machine learning algorithm. An accuracy metric is used to measure the algorithm’s performance (accuracy) in an interpretable way. It goes against my intuition that these two sometimes conflict: loss is getting better while accuracy is getting worse, or vice versa. I’m working on a classification problem and once again …
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