Questions tagged [mae]
The Mean Absolute Error (MAE) is a point forecast accuracy measure. In the forecasting literature, Mean Absolute Deviation (MAD) is used interchangeably.
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What does it mean for the RMSE to be the same as the mean of the range?
I made some predictions on some time series data. The plots look good, the predictions line up with the original values quite well. But the error values don't make much sense to me. I calculated the ...
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What is the interpretation of the negative value for the Normalized Mean Absolute Error (nMAE) metric?
I am using the normalized mean absolute error metric for evaluating my results. The data I use is in time-series form. Their trend may be increasing or decreasing over time. All the values are ...
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Can MAE be reported in percentage?
In Wang et al. "Predicting New Workload or CPU Performance by Analyzing Public Datasets" (2019), the MAE is measured in a standardized space (Mean=0, SD=1). This is discussed in 3.4 Metrics, ...
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40 views
MAPE is better but MAE is worse in regression models
I am working on a regression problem to predict price of the vehicle based on its features. I have been experimenting with several trials but in one of them, MAPE (Mean Absolute Percentage Error) is ...
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33 views
How to choose between MSE,MAE, RMSE and RMSLE? [duplicate]
Mean Absolute Error (MAE) measures the absolute average distance between the real data and the predicted data, but it fails to punish large errors in prediction.
Mean Square Error (MSE) measures the ...
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63 views
What is mean average error?
I saw that in some articles but I couldn't find any definition. Its unit is in the following form:
MAE/mean(MAE)
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35 views
huge difference between RMSE and MAE in non-linear regressors
I am building non-linear regression models such as a Random Forest regressor , a KNN regressor or a SVM using a RBF kernel and I decided to use both RMSE and MAE as evaluation metrics.
I know that a ...
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34 views
Mean average error normalized by the standard deviation of the target
I'm working on a regression model, aiming at prediction age from structured data.
I'm using the mean average error (MAE) as evaluation metric, and want to compare my performances with state-of-the-art ...
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1answer
75 views
MAE regression gives biased regression parameters for symmetric error?
Consider a linear model,
$$
y_i = \beta_0 + \beta_1x_{1i} + \beta_2x_{2i} + \epsilon_i.
$$
From the Gauss-Markov theorem, I know that, under nice conditions, the $\hat{\beta}_{OLS}=(X^TX)^{-1}X^Ty$ ...
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How should i compare this MAE results
I'm in need of help to correctly interpret these results.
I am analyzing a time series of crime data. The series has 351,980 events.
These are the results of the predictions using a regression model:...
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1answer
729 views
How do I interpret mean absolute error (MAE) or mean absolute percentage error (MAPE) in layman words?
For example, I am predicting a score that can have value from 0 to 100. Lets assume MAPE = 10...
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54 views
Scaling the MAE by the mean of non zero points for intermittent data
I am currently trying to find a way of scaling the MAE for my intermittent data.
The data is always greater than 0 and is intermittent, with long periods of zeros.
I have read a few papers that ...
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1answer
51 views
What does it mean when MAE improved while RMSE worsened?
I am comparing two models:
One is a black box that I cannot understand, the other is a GLM.
How can I describe why the differences are like this? Is the GLM performing worse than the blackbox?
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180 views
Quantile loss 50th is MAE, is it? [duplicate]
I'm not sure the above sentence is true, but I read it here, here and here that quantile loss function percentile 0.5 is MAE(mean absolute error), Is it true(Yes or No)? and How?
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148 views
Comparison of MAE and Mean to illustrate the error magnitude
I have predicted a time series with positive, zero and negative values. As error measurement I used the Mean Absolute Error (MAE).
In order to give the reader of my paper a better understanding ...
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1answer
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Learning Curves using different models
I am running repeated K-fold Cross-Validation on my dataset using different models. My problem is a regression problem and I am counting on the error metric MAE. I do know that some models may behave ...
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Can someone give the intuition behind Mean Absolute Error and the Median? [duplicate]
I do not understand the intuition behind why the median is the best estimate if we are going to judge prediction accuracy using the Mean Absolute Error. Let's say you have a random variable $X$ and ...
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1answer
216 views
Dividing the MAE by the average of the values
I would like to parse the MAE (Mean Absolute Error) to a percentage value. I know there is the MAPE (Mean Absolute Percentage Error), however it has some drawbacks as going to infinity if one of my ...
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Can RMSE and MAE have the same value?
I am implementing cross validation and calculating error metrics such as RMSE, $R^2$, MAE, MSE, etc.
Can RMSE and MAE have the same value?
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193 views
RSME, MAE and prediction interval [closed]
Could someone please clarify, whether it is appropriate to define a prediction interval or an equivalent for an RMSE and MAE measure. If so, could you please suggest how such an interval is defined.
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226 views
MSE Intuition and Interpretation
I've got a very small question. Say I'm making a linear regression model. When I test the model with a testing set, I get an MSE of 4.31 (arbitrary). What do I interpret from this? As in, what does ...
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75 views
Error distribution for Huber Regression
For linear regression there's an assumption that error terms come from normal distribution. so that $Y = aX + b + \epsilon$, where $\epsilon$ has normal distribution with mean zero and certain ...
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1answer
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a measure for MAE (of a regression)
I'm running a grid search, in order to fine-tune a NN hyper parameters.
the question is:
the MAE values I get from the trainings are too close.
since I have the statistical attributes of the target ...
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3answers
687 views
Standardised mean absolute error (SMAE) and how to calculate it?
I am using the mean absolute error
mean(abs(obs - pred))
as one of the measures assessing the fit of my model. I would also like to have a standardised measure ...
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269 views
What is the best point forecast for gamma distributed data?
I believe that the values I am forecasting are gamma distributed with shape $k>0$ and scale $\theta>0$. I need a point forecast (i.e., a one-number summary) that minimizes the expected error. ...
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What is the best point forecast for lognormally distributed data?
I believe that the values I am forecasting are lognormally distributed with log-mean $\mu$ and log-variance $\sigma^2$. I need a point forecast (i.e., a one-number summary) that minimizes the expected ...
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1k views
calculating overall error in k-fold cross validation
when using k-fold cross validation i thought the overall error was equal to the mean of errors of each fold. the error being anything from MAE and RMSE to NDCG,F-measure, precision and recall. however ...
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1k views
Mean Absolute Error in Random Forest Regression
I am new to the whole ML scene and am trying to resolve the Allstate Kaggle challenge to get a better feeling for the Random Forest Regression technique.
The challenge is evaluated based on the MAE ...
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1answer
41 views
What statistical test do I need for comparing forecasted data with actual data?
I’m currently completing my dissertation and need to compare forecasted wave height to the actual wave height.
However I am unsure what statistical test to use.
Thanks,
Jess
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Does normalisation affect the values of Mean Squared Error, Mean Absolute Percentage Error etc.?
I have a large amount of data, divided into folders and files. Each file has 56 features/columns and around 10,000 rows. The data is normalised (values between -1 and 1) and some of the features have ...
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3answers
5k views
Why does minimizing the MAE lead to forecasting the median and not the mean?
From the Forecasting: Principles and Practice textbook by Rob J Hyndman and George Athanasopoulos, specifically the section on accuracy measurement:
A forecast method that minimizes the MAE will ...
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1answer
323 views
MSE or MAE absolute and relative performance
I'm comparing different ARMA-GARCH specification out-of-sample in order to understand whether the more "parsimonious" models prescribed by BIC do not perform more poorly than the more "expensive" ones ...
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MAE and Precision for Collaborative Filtering Recommender Systems
I have got a question concerning Recommender Systems and Evaluation Metrics. I tested a few collaborative filtering recommendation algorithms on dataset containing amazon ratings.
Here you can see MAE ...
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9k views
Mean Absolute Error (MAE) derivative
$MAE=|y_{pred} - y_{true}|$
$\dfrac{dMAE}{dy_{pred}} = ?$
I'm trying to understand how MAE works as a loss function in neural networks using backpropogation. I know it can be used directly in some ...
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1answer
115 views
improve performance in a regression methodology
I'm performing my own nonparametric regression in matlab and I'm wondering to switch one nuance of my methodology:
Methodology:
split Training/test set (i.e. 80/20 %)
search the best gamma ...
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Why does the MAE of my estimation improve substantially when I divide it by 10 (in a very noisy dataset)?
I have an extremely noisy dataset, and I try to minimize the MAE. Apparently, when my linear regression makes its prediction - it has something like -1000 MAE (when compared to the MAE of an all-zero ...
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Can RMSE be smaller than MAE?
Generally speaking, can RMSE be smaller than MAE?
I am calculating RMSE and MAE for my results. In two out of five methods, the RMSE is smaller than MAE. Note that I am using the same data, the same ...
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Is there an analog for the coefficient of determination with absolute error?
Typically to measure the predictive power of a model, R^2 is more useful than RMSE because a RMSE score isn't very meaningful without a basis of comparison. If you are using mean absolute error (MAE) ...
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874 views
MAE has gotten worse but RMSE is better, how should I interpret it?
I am doing some testing in recommender systems with extended epinions dataset, I implemented two models, model A give me RMSE of 0.5387 and MAE of 0.3111 and model B gave me RMSE of 0.5121 and MAE of ...
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L1 (MAE) vs L2 (MSE) when data is normalized between 0 and 1
In most of the literature, it is emphasized that the L2 norm (MSE) gives a higher error when dealing with outliers compared to the L1 norm (MAE).
But what happens when we normalize the data between 0 ...
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1answer
1k views
Can MAPE Decrease while StdDev Increases?
Can a decrease in mean absolute percentage error (MAPE) be correlated with an increase in standard deviation of the error? Is that counter-intuitive? What about MAPE vs. mean absolute error (MAE)? I'm ...
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1k views
Mean Absolute Error Cost Function in Logistic Regression
Is there any reasons not to use MAE as cost function in logistic regression?
Yes, I know about problems with optimization, I know that this estimation won't be max-likelihood estimation.
But is there ...
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1answer
315 views
Best imputation techniques (error test)
actually my study is about to choose best imputation techniques. Im comparing all the techniques using Root Mean Square Error (RMSE), Mean Aabsolute Error (MAE) and correlation (R). My problem is ...
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1answer
1k views
What is the point of Root Mean Absolute Error, RMAE, when evaluating forecasting errors?
RMAE is defined as the square root of the Mean Absolute Error (MAE). Presumably this is by analogy to Root Mean Square Error (RMSE) being defined as the square root of Mean Square Error (MSE).
But ...
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1answer
52 views
Error measure that take the time of prediction into account?
I am doing a machine learning project where I'm attempting to predict the arrival times of buses equipped with GPS at bus stops, and I am very new to statistics/data analysis. I am looking for an ...
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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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1answer
465 views
Relatively low MAE, but also low R-squared? Why
I am testing forecasts against against realized values with a number of observations of 4000.
When I calculate the mean MAE, its relatively low. Around 10% deviation to the original variable.
...
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2answers
1k views
Using GARCH rolling forecast in R to calculate MAE?
My intention is to calculate the MAE for different (G)ARCH-models (comparing the one-step-ahead forecast for $\sigma$ with the absolute return that day).
The formula for MAE is actually clear, but I'...
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597 views
Large-scale MAE regression in R
I have a large, sparse dgCMatrix matrix in R:
~200,000 rows
~150,000 columns
~1,000,000,000 non-zero entries
R code to generate the matrix:
...
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2answers
362 views
How to check if specific MAE and MSE are feasible given only the real data?
I have as data some real measures, let's say: 1000, 800, 900, 1100, 900 and I have the Mean Absolute Error (MAE) and Mean Squared Error (MSE) 80 and 20000, but I don't know which are the estimated ...
