Linked Questions
36 questions linked to/from Mean absolute error OR root mean squared error?
40
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7
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Why is using squared error the standard when absolute error is more relevant to most problems? [duplicate]
I recognize that parts of this topic have been discussed on this forum. Some examples:
Is minimizing squared error equivalent to minimizing absolute error? Why squared error is more popular than the ...
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1
vote
1
answer
4k
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Higher RMSE but lower MAE and RMLSE. Which model is better? [duplicate]
I am evaluating two machine learning models. The output is count data which has a range of 0 to 30, which most of the output values being small values. Large output values are rare.
One model has ...
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0
votes
1
answer
4k
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What to check in cross-validation - MAE or MSE? [duplicate]
When using cross-validation for model selection, should one look at MSE or MAE. I know that MSE and MAE are related but which is the more appropriate measure?
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0
votes
1
answer
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how to pick model, MAE or rMSE [duplicate]
Im building two models, (model1 and model2)
I trained and tested them on the same test dataset,
model1 will have mean absolute error (MAE) 10.3, rooted mean squared error (rMSE) 30.1
model2 will have ...
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0
votes
2
answers
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MAE or RMSE for my data? [duplicate]
I have been checking how each error metric works in the hope to find the best one for my data but it can be quite tricky actually.
I have monthly time series data and I am running a SARIMA model to ...
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0
votes
1
answer
594
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Why RMSE over MAE for matrix factorisation? [duplicate]
I have been trying to compare several matrix factorization algorithms and I've noticed that all the papers and libraries I've seen measure the Root Mean Square Error(RMSE) when intuitively I would ...
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35
votes
5
answers
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Why do we take the square root of variance to create standard deviation?
Sorry if this is has been answered elsewhere, I haven't been able to find it.
I am wondering why we take the square root, in particular, of variance to create the standard deviation? What is it about ...
- 2,651
9
votes
3
answers
5k
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L1 & L2 double role in Regularization and Cost functions?
I'm confused about the way L1 & L2 pop-up in what seem different roles in the same play:
Regularization - penalty for the cost function, L1 as Lasso & L2 as Ridge
Cost/Loss Function - L1 as ...
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11
votes
3
answers
6k
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Why there is square in MSE (mean squared error)?
Please forgive me for such a beginner question, since I'm learning stats . & machine learning.
I'm trying to understand Mean Squared Error.
I understand the "Mean Error", the Mean of Errors ...
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8
votes
2
answers
881
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Which metric to use for estimating accuracy of a climate model?
Let's assume I have 3 different climate models for a specific region that project the temperature. I also have the observations of that region for the same time frame(the real temperatures). My ...
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8
votes
2
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A universal measure of the accuracy of linear regression models
I have a dataset that contains both outliers and multicollinearity.
I applied three different regression models to that dataset: ordinary least square, absolute linear regression, and Huber regression....
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7
votes
1
answer
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F1 score, PR or ROC curve for regression
Due to my background as a pure biologist, I've been struggling with the comment acquired from a reviewer about the accuracy test used in my regression study. While I stick to MSE, MAE and R2 as the ...
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4
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2
answers
2k
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RMSE - where this evaluation metric came from?
Does anyone know where this metric came from ?
Can someone bring article references or something like this?
Im actually wondering if there's any mathematical concept or any way to demonstrate ...
- 641
2
votes
1
answer
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Mean Squared Error changes according to scale of value in machine learning regression problem
I am working on a machine learning regression problem and I have chosen the metrics Mean Absolute Error (MAE) and 'Mean Squared Error (MSE). I have 3 features and two of them have values in the range ...
user292709
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vote
2
answers
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Should I convert the number after log transformation back to the original for calculating RMSE?
When I built the model, I applied the log transformation to all variables including the dependent variables. Now, I'm calculating the RMSE for the evaluation, and the result is in the log format, ...
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