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Feb 26, 2021 at 2:50 answer added Brian Spiering timeline score: 0
May 10, 2020 at 4:17 comment added Dave RMSE is a MEAN error. It divides by the number of observations: $$RMSE=\sqrt{\dfrac{\sum_{i=1}^N\big(y_i-\hat{y}_i\big)^2}{N}}$$As far as wanting to penalize large errors at shallow depths more than large errors as deep depths, that makes more sense. Mean absolute percentage error sounds like a good place to start. Its known issues are discussed in its Wikipedia article, and alternatives are proposed.
May 10, 2020 at 4:02 comment added Chris @Dave for water depth 25-30 m, I have ~50 observations, and for other lower depth ranges I have as high as 300 - I have an increment of 5m (i.e., 0-5, 5-10, 10-15...). RMSE is ~ 1m for other depth ranges, but ~6m for depth range 25-30. I know error is overall and will depend on number of points that are predicted well. I want a metric that will take the large error of ~6m at 25-30 m depth range into account.
May 10, 2020 at 3:45 history edited ebrahimi CC BY-SA 4.0
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May 10, 2020 at 3:40 comment added Dave Why do you think that your metric depends on the number of observations?
May 10, 2020 at 2:46 review First posts
May 10, 2020 at 3:45
May 10, 2020 at 2:41 history asked Chris CC BY-SA 4.0