Linked Questions

1
vote
1answer
17 views

Find the value that occurs most frequently or use the average?

If I were trying to predict the next number in a list of numbers based on past performance would it make sense to find the number that has occurred most frequently? For example, if I were to say based ...
18
votes
3answers
2k views

(Why) Is absolute loss not a proper scoring rule?

Brier score is a proper scoring rule and is, at least in the binary classification case, square loss. $$Brier(y,\hat{y}) = \frac{1}{N} \sum_{i=1}^N\big\vert y_i -\hat{y}_i\big\vert^2$$ Apparently this ...
0
votes
1answer
210 views

Expected Predicted Error (EPE) with L1 loss

In Element of Statistical learning it is saying on page 20, equation 2.18. That using the L1 norm instead of the usual L2 norm leads to an $f(X)$ optimising the EPE being the median instead of the ...
2
votes
2answers
40 views

Practical use of median?

Someone recently asked me the business use of various measures of central tendencies. Although the usage of mean and mode is intuitive and easily seen, I could not think of one intuitive use of median....
0
votes
1answer
23 views

Does quadratic loss find the median of the prior distribution?

Does quadratic loss find the median of the prior distribution? Someone told me linear loss finds the mean, all-nothing loss function finds the mode of the prior.
3
votes
1answer
774 views

Higher RMSE lower MAPE

I have a time series model that forecast next K days. For example when I forecast next 50 days my MAPE is 20.3% and RMSE is 2943 and when I forecast next 200 days is the MAPE is 10.25 % but RMSE is ...
1
vote
1answer
348 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?
0
votes
1answer
473 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 ...
19
votes
2answers
2k views

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 ...
4
votes
1answer
1k 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 ...
2
votes
1answer
29 views

Compare value with distribution

I have developed a model that returns flight times between two airports e.g. Paris Rome, 115 minutes. I would like to compare this value with the value distribution from real flights e.g. (123, 110, ...
1
vote
2answers
868 views

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, ...
2
votes
1answer
38 views

Error measure for 3D-field-comparison - meaning of mean/median

Short Version I have to compare two vectors of predictions (from different methods) against one vector of measurements to find out which prediction performs better. Note that this is not a ...
2
votes
1answer
288 views

Predictive distribution: What can we say about the prediction?

I am wondering what could we obtain more from the predictive distribution. Give a set of data, say $\mathcal{D}=\{(x_i,y_i)\}$, we want to predict the value s$Y_{new}$ at new locations, say $X_{new}$. ...
2
votes
1answer
427 views

Need advice on evaluating forecast accuracy in R

I'm trying to evaluate some software for forecast accuracy. It works by summing up all the orders from a number of locations for each month, then determines the best model out of a series of models ...

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