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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41 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
52 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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734 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
55 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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44 views

How do I weight multiple forecasts based on Mean Absolute Percentage Error (MAPE)?

I have 3 forecasts that have different Mean Absolute Percentage Error values that were averaged for each forecast over a 6 month period at a monthly cadence against end of month actuals. How would I ...
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1answer
219 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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58 views

Evaluating GARCH Model

I used ugarchroll to backtest my garch model on S&P returns. This is my code: ...
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1answer
500 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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51 views

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
110 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
18 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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1answer
1k views

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
111 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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96 views

MAPE vs R Squared, and their Interpretation in Regressions

So, I'm somewhat familiar with R squared and MAPE, and their usage to qualify the goodness of fit for a regression model. My question is not about when to use one or another (like in this post) but ...
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0answers
148 views

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
23 views

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
83 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
327 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
158 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
179 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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45 views

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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1answer
201 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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203 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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36 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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1answer
584 views

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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51 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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657 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
9k 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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120 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
8k 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
386 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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27k 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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146 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
5k 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
15k 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 ...
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1answer
2k views

Compute MAPE with negative actual values

I am training a residual data with negative values through ANN. So I partition my data with 20 values for testing. But what I get in my MAPE is a negative value. Here is my data: ...
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2answers
6k views

What is the acceptable level of accuracy while doing Weekly Time Series Forecast

I'm doing a weekly time series analysis and I'm generally getting a mape of 35% is that ok according to the industry standard?
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1answer
987 views

Is R2 useful to determine the accuracy of VARX model?

I have a VARX model with 3 endogenous variables in 2nd differences. Each of 3 equations has very low $R^2$ (about 0,02), but the model gives good forecast (MAPEs are about 2%). Can I neglect low $R^2$ ...
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0answers
239 views

Which prediction model is better for this rolling time series prediction?

The aim is to predict the breakdown time of a machine as a percentage of scheduled hours for the next day. So my time series looks like this, Break_down_percentage = 7%, 8%, 10%, 6%, 12 % etc. There ...
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2answers
4k views

Difference between forecasting accuracy and forecasting error?

I am working on a demand forecasting project and I am puzzled by the client's standards of forecast evaluation. The MAPE (Mean Absolute Percentage Error) with the sample data Forecast = 300 and Demand ...
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230 views

mape and mae from k-fold backtesting on time series

I performed a rolling window (i.e. do full sample, then next 4 observations until the last, and so on...) k-fold test for out of sample testing due to limited number of observations. From the MAPE ...
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2answers
1k views

ARIMA model with huge MAPE value

I have a question about the role of the MAPE in the ARIMA model optimization. For a daily time series I have found that the best model (using the Box-Jenkins approach) is an ARIMA(7,0,7)(0,0,0). If I ...
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1answer
776 views

Applying different time series models (ARIMA, HOLT-WINTER) on the basis of MAPE

I have a time series object calc_visit_ts. I want to apply the best fit time series model based on the MAPE value for each model. The issue I face is that the MAPE ...
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2answers
8k views

Best way to optimize MAPE

The MAPE is a metric that can be used for regression problems : $$\mbox{MAPE} = \frac{1}{n}\sum_{t=1}^n \left|\frac{A_t-F_t}{A_t}\right|$$ Where $A$ represents the actual value and $F$ the the ...
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1answer
28k views

Calculating MAPE [closed]

Is the below calculation of the Mean Absolute Percentage Error MAPE correct? I've included a workable example, but really the lines in question are these: ...