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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Why RMSE and MAPE changes with the change of axis?
I need your help regarding the information inside the picture. As you know all the information will change with the change of NDVI axis from y-axis to X-axis, except R2 and p-value remain the same? ...
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Is Median Absolute Percentage Error useless?
I'm working on a project focused on pricing houses.
Looking online I see a lot of works and companies providing the performances of their model using the median instead of the mean (see for example ...
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Does weighted MAPE (wMAPE) provide an accurate estimate of error?
I'm trying to use wMAPE to calculate demand standard deviation for future forecasts, however, the wMAPE that we are using is derived from 13 buckets of actuals over a period of 52 buckets of time. If ...
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Diebold-Mariano test gave a p-value of 0.033. What are the conclusions?
After performing a Diebold-Mariano Test i got a p-value of 0.03345.
Can i concluded that Based on Diebold-Mariano test, we reject H_0 for the significance levels of 5% so that the accuracy of the ...
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How do we compare MAPEs?
if we have two models M1 and M2:
MAPE_{M1} = 100%
and
MAPE_{M2} = 70%$
Does that mean that M2 is better than M1? can we say that M2 is (100/70 -1)*100 = 43% better?
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Does it make sense to increment by 1 the numerator and denominator in the MAPE to avoid division by 0?
One of the drawbacks of MAPE is that you can have actuals equal to 0. This will result in a division by 0 and thus an undefined MAPE. Does it make sense to increment by 1 the numerator and denominator ...
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Best point forecast for MAPE
I have a data that can have different distribution.
For example every time I get a set of different data :
1, 2, 3, 4. I use metric MAPE and try to find best point to minimize my MAPE. Is there a ...
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How can I modify the mean absolute percentage error to account for the curve direction?
I am trying to predict the trend of a certain curve in the future (whether it will be increasing, decreasing, or remain constant). For evaluating my prediction, I am using the mean absolute percentage ...
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MAPE does not take into account the range of the output?
I have a time-series regression model where the output is always in the range of 6000-6050. After training my model, I get a Mean Absolute Error of around 18 and hence, very low Mean Absolute ...
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when i have to calculate mape rmse before or after inverse_transform
hello i want to know when i have to calculate mape rmse before this code
predictions1 =scaler.inverse_transform(predictions)or after it. because the result is ...
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Generating random samples that satisfies specific r-squared of MAPE
I would like to generate some samples that satisfies a specific r-squared or MAPE(Mean Absolute Percentage Error) with a given vector.
For example, a vector a_i is given and I want to generate some ...
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Alternative to mean absolute percentage error (MAPE)
MAPE metric has problems when the actual value to be predicted is very small. In the extreme when the actual value is 0 then MAPE will be infinity (if the prediction is not exactly 0). What about this ...
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MAPE comparison between 2 or more runs of model
I am new in analytics field.
Our team runs multiple model which does the demand forecasting for multiple product.
To check whether the model is performing good or bad we calculate the MAPE and decide ...
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RMSE or MAPE? which one to choose for accuracy?
I have a weekly times series for which I would like to find the best fit model. So far I've tried arima, Harmonic regression with arima error, neural network and in the end I would like to decide ...
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Accuracy percentage-wise of a regression model [duplicate]
I would like to check in percentage the accuracy of my regression model. I know that normally accuracy is used as a metric for classification. I have evaluated my model based on r-squared and also ...
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Facebook prophet gives a very high MAPE, how can I improve it?
I have some daily sales from 2018-01-01 to 2021-10-21 and I'm trying to predict the sales a year into the future. I opted for facebook prophet. My raw data looks like this:
According to a DF-test, ...
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What if a seasonal naive model is the best model?
I ran 10 years worth of monthly data (first 7 years train, next 3 test), through 8 forecasting algorithms:
SARIMA, ETS, HW, Seasonal Naive, NNETAR, Prophet, TBATS, and VAR.
For most of these, where ...
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In-Sample and Out-of-sample forecasting accuracy
I am currently doing my college final project. I forecasted national soybeans yield and used MAPE to calculate the in-sample and out-of-sample forecasting accuracy. The MAPE results showed that the in-...
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How to force a neural network to uniformly decrease MAPE?
I aim for replicating an numerical (non stochastic) algorithm by a neural network. Therefore I have basically an unlimited amount of data and I wish that the network have an almost perfect fit in ...
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Why the prediction of this Random Forrest model is so poor?
I am using Random Forrest to predict the MRR (Material removal rate). But the predictions have been quite off the mark. Even Linear Regression gave a much better result. I don't know where I'm going ...
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Can MAPE values change after inverse tranform of target?
I have tranformed my Target variable as following Maxmin transformation and used an engine to get prediction for a time series data. The target transformation is done using the following formula in ...
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When does MAPE (Mean Absolute Percentage Error) fail?
I have a multioutput regression model that predicts float values. When using MAPE to evaluate regression model performance (using either built in libraries or implementing a function for it) I am ...
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MAPE vs. SSE error minimization on generated data from a function?
I have a question regarding the performance of MAPE and SSE in fitting datasets generated from another equation.
I have the following equation (I am truly sorry, I do not know how to write in LaTeX):
...
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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