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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 ...
1 vote
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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 ...
4k views

### 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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### 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 ...
522 views

### 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 ...
320 views

### 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 ...
35k views

### 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 ...
5k views

### 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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### 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 ...
762 views

### 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 ...
3k views

### 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 ...
2k views

### 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 ...
1 vote
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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, ...
10k views

### 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 ... 1 vote