Questions tagged [mape]

The Mean Absolute Percentage Error (MAPE) is a point forecast accuracy measure. As a percentage, it can be compared between forecasts for time series on different scales, and it is easily interpreted. However, it is asymmetric (underforecasts' MAPEs are bounded at 100%, while overforecasts' are unbounded), potentially leading to biased forecasts. The MAPE is undefined if any actual is zero.

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28 views

Mean absolute percentage error with respect to predictions

A friend of mine has suggested that instead of using mean absolute percentage error, i.e. $$ \frac{1}{N}\sum_{i=0}^N \left| \frac{A_i - P_i}{A_i} \right| $$ (where $A_i$ denotes an actual value, $P_i$ ...
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What is “symmetry” in evaluation metrics

I'm seeing Mean absolute percentage error (MAPE) is not symmetric. Tried to understand what is symmetry here but didn't find a good answer online. Can I ask: What is symmetry in evaluation metrics? ...
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Is this the right way to evaluate MSE, RMSE, MAE, MAPE after creating a model on data passed through a standard scaler?

Create the Scaler object scaler = preprocessing.StandardScaler() Fit your training data on the scaler object ...
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23 views

Low value on MAPE when using log CPI

I'm trying to evalute my Holt-Winter model using MAPE (mean absolut percent error) and I'm getting a low value at 0.2% which seems a bit too low. I'm using data on CPI from Belgium (per month) where I ...
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15 views

Acceptable range for sMAPE measure [duplicate]

Defining sMAPE as $$sMAPE=\frac{2}{h}\Sigma_{t=n+1}^{n+h}\frac{\left\lvert Y_t-\hat{Y_t}\right\rvert}{\left\lvert Y_t\right\rvert+\left\lvert\hat{Y_t}\right\rvert}*100$$ where $Y_t$ is the value of ...
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24 views

Where is appropriate to use sMAPE performance measure?

I have a code which predicts values using three different models: lm, auto.arima and ...
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14 views

What is the difference between correlation and mean absolute percentage error? [duplicate]

So here is my question, I have to columns of data. One of them is a black box model's output, and the other one is my actual numbers. The correlation between these two columns is 99%, but the MAPE is ...
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2answers
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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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1answer
186 views

Finding a confidence interval of a MAPE

First time posting. I have two columns of data, one for the model output and one for the actual data that has come in. I calculated the MAPE and got a percentage. I performed the following analysis, ...
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1answer
14 views

Own model accuracy measure for regression analysis

Is it possible to produce an own model accuracy measure that takes 100% - MAPE? If MAPE is 5 % for example, the model accuracy would be 95%? Or is that statistically incorrect?
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886 views

Mean Absolute percentage error getting infinity?

i have written a function for calculating mape using python here i am mentioning the function : ...
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266 views

Is there any standard / criteria of good forecast measured by SMAPE and MASE?

I have built a forecasting model for a company. Since it is dedicated to practical usage, I prefer to use the relative error parameter (like MAPE, SMAPE, & MASE) as a measurement for my model ...
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1answer
134 views

Is this the correct place to use MAPE as a loss function?

I've made a neural network designed to do regression. However, my dataset is unbalanced, and the data in the smaller section of the dataset have very different target values than the target values in ...
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2k 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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1answer
133 views

Over-fitting SARIMA model

I am currently running an iterative process(for loop) to determine best ARIMA model for monthly sales data according to smallest AIC and MAPE. Box-Jenkins methodology clearly states to choose the ...
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2k views

Mean absolute percentage error returning NAN in PyTorch [closed]

I'm using mean absolute percentage error (MAPE) as a loss function for an RNN, however during training I start getting NaN values. I first used MAPE to calculate error between sequences of 3D ...
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1answer
158 views

Acceptable Standard for MAPE

What is the general acceptable value of MAPE in industry ?. I am getting MAPE of around 24% on live data that has 48 data points in which 42 as train data and 6 as test data. I am trying to do ARIMA ...
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434 views

MAPE and SMAPE shift invariance (bias)

MAPE (Mean Absolute Percentage Error) and SMAPE (Symmetric Mean Absolute Percentage Error) both are sensitive when the TRUE ...
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1answer
1k views

WMAPE / WAPE for the evaluation of time series with positive and negative values

I have a time series y that has both positive and negative that I want to predict. For the prediction I normalize the values to a range between 0 and 1. If I give ...
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38 views

What is a Good Error Target

I am modeling a forecast for product categories using auto Arima in R. I'm getting MAPE of between 9-15% on average. We don't have any historical records of forecasts vs actual so I don't know how ...
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Which average to use to summarise multiple MAPE values?

Suppose you have a model, evaluated using mean absolute percentage error (MAPE), that has made predictions on 1000 different examples. Each example will have an associated MAPE that reflects how well ...
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1answer
309 views

Why forecast::accuracy() mape is working with 0/0?

I'm learning now some metrics of goodness about time series forecasting, using the forecast package, but I'm stuck in something that surely I've not understood well....
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1answer
29 views

Recency weightage on stock forecast error

Say I want to forecast retail stock for 1 month, on daily basis. The error will be calculated using SMAPE, but I would weight the error using recency, i.e., the nearer the weight from now the higher ...
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How do I decide when to use MAPE, SMAPE and MASE for time series analysis on stock forecasting

My task is to forecast future 1 month stock required for retail store, at a daily basis. How do I decide whether MAPE, SMAPE and MASE is a good metrics for the scenario? In my context, over-forecast ...
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1answer
286 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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sMAPE and MAPE with negative values

I have a time series data that is not stationary (with trend and seasonal components) so in order to make it stationary, I've applied a difference transform of 1. Due to this effect, some negative ...
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1answer
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Good metric to assess error in estimating a value

So this seems like a simple question, but I cant find a way to solve it or formulate a solution that makes sense. My case is that I have an algo that detects fuel theft (ft_calc). Now I want to ...
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1answer
177 views

Can I use sMAPE when my actuals and prediction have postive and negative values?

I used several datasets and make predictions on it with many algos (ARIMA, Theta, Smoothing, etc.). Until now the current outome as well as the predictions (of the datasets) were strictly positive (...
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1answer
967 views

How to optimize MAPE in regression algorithms

I have a regression task where the label is varying from about 0.001 to 1000. One of the feature called group, for example, group A corresponding label from 0-0.1 and group G corresponding label from ...
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1answer
335 views

Why is the MAPE exceptionally high [closed]

error on test set: [2442.239337101689, 29.913345202693232, 5162219874.342154] These are the results on the test test for a regression problem. The first two ...
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2answers
334 views

“Percentage” alternatives to MAPE

I'm aware of the problems of MAPE as a measurement, and particularly it's uselessness in the event of a time series where 0 is one of the many values of y. The downside to ditching MAPE in favour of ...
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Why am I getting better MAPEs when running an ARIMA model on a non-stationary time series (vs. a stationary one)?

I've been using ARIMA modelling to predict the number of orders a business receives. I have data for 3 years, and the time series shows a strong (uneven) upward trend, with increasing variance over ...
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288 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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2answers
354 views

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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1answer
44 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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173 views

How correctly overcome problem with an infinity MAPE? [duplicate]

Should I choose an other metric or is the way to handle this problem?
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832 views

why is the MSE error higher than MASE and MAPE?

I have a product price time series when I apply two models on them, I calculate all of MSE (Mean Squared Error), MASE (Mean Absolute Scaled Error), and MAPE (Mean Absolute Percentage Error). I noticed ...
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2k views

Interpretation of Theil's U2 Statistic - “Forecasting Methods and Applications” book

I was reading "Forecasting Methods and Applications" book and came across Theil's U statistic formula. I am facing difficulty in understanding the interpretation of Theil's U statistic. According to ...
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1answer
12k views

MAPE Value more than 100% [closed]

Im using Trend Analysis - Double Exponential Smoothing Plot (not seasonal and it has a trend testedly) to forecast the net amount of carrier switchers (using Mobile number portability) in the future ...
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133 views

MAPE yielding value of 1000+ for timeseries forecasting

I am comparing a model's outcome with the actual values for a span of 9 months. I am expecting a very large error, however my MAPE implementation yields 1404512.56 using python, pandas. Here is my ...
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1answer
11k views

MAPE vs R-squared in regression models

Usually regression models are evaluated using $R^2$. I understand this metric can be misleading too at times but as far as I understand the first parameter we look at is $R^2$. There is another ...
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1answer
581 views

Is MASE specified only to time series data

Will it be correct to use Mean absolute scaled error in non time series data? I've got a set which contains a lot of zeros, so errors like MAPE can not be used here. MASE based on difference between ...
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1answer
2k views

Gradient and hessian of the MAPE

I want to use MAPE(Mean Absolute Percentage Error) as my loss function. ...
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1answer
2k views

Relationship between forecast bias and accuracy for situations with constrained supply

Consider a forecast process which is designed to create unconstrained end-customer demand forecast. This means that the forecast generation process does not consider supply or distribution constraints....
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37k views

What are the shortcomings of the Mean Absolute Percentage Error (MAPE)?

The Mean Absolute Percentage Error (mape) is a common accuracy or error measure for time series or other predictions, $$ \text{MAPE} = \frac{100}{n}\sum_{t=1}^n\frac{|A_t-F_t|}{A_t}\%,$$ where $A_t$ ...
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156 views

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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3answers
6k views

Meaning of Min/Max Accuracy of a regression model

I'm trying to measure the accuracy of some linear regression models I fitted in R. I ran into this page offering a technique called Min_Max Accuracy which is ...
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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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1answer
19k views

Is MAPE a good error measurement statistic? And what alternatives are there?

I have a time series that deals with rainfall. It is a period of 10 years (daily resolution), and covers climate variables. I'm going to feed the data into an Artificial Neural Network to predict the ...