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2 votes

Calculating accuracy of prediction

I'll take a somewhat different track from Demetri. There are multiple aspects here. A best quantification of prediction accuracy is surprisingly tricky. An accuracy measure is, for practical purposes, ...
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2 votes

Calculating accuracy of prediction

Is it possible to restrict such a quantification to a range between 0 and 100%, such that a correct prediction (20%) would evaluate to a 100% accuracy? I don't believe so. What you're asking is &...
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1 vote
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How to combine accuracy scores of two models. Same samples with different output values

You cannot just multiply the two accuracies. Imagine both models to be correct on exactly the same inputs, which is maybe 50% of all inputs, then the two models would each have an accuracy of 0.5, as ...
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0 votes

Forecast accuracy metric that involves prediction intervals

Maybe you could try with Winkler scores. Quote from A brief history of forecasting competitions: For interval forecasting, Winkler scores (Winkler 1972) have been widely used, but are not scale-free. ...
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Why not use evaluation metrics as the loss function?

It's because accuracy is not a proper scoring rule. You will want to consider the cost of misclassification. Here are some more useful links: Example when using accuracy as an outcome measure will ...
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18 votes

Why not use evaluation metrics as the loss function?

Maximizing accuracy (percent of correctly examples) is the same as minimizing error rate (percent of incorrectly classified examples). For a single observation, the loss function for the error rate is ...
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