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[D] Rich model/Poor model: Logarithmic Loss and comparing model performance – an exploratory analysis

I was reading about logarithmic loss and I became curious about a few things, so I did an exploratory analysis using a “good” model and a “bad” model.

Some things I looked at include: distribution of log loss, mean vs. median and calculating it separately for the target and non-target classes.

I’d like to know if anyone has any thoughts or ideas to discuss regarding some of the more nuanced aspects of the metric.

https://emilyswebber.github.io/LogLoss/

submitted by /u/datadatadata84
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.