Shepperd and MacDonell “Evaluating prediction systems in software project estimation”. Information and Software Technology 54 (8), 820–827, 2012, proposed an improved measure of the effectiveness of predictors based on comparing them with random guessing. They suggest estimating the performance of random guessing using a Monte Carlo scheme which unfortunately excludes some correct guesses. This...

Several wavelet synopsis construction algorithms were previously proposed based on dynamic programming for unrestricted Haar wavelet synopses as well as Haar synopses. However, they find an optimal synopsis for every incoming value in each node of a coe cient tree, even if di↵erent incoming values share an identical optimal synopsis. To alleviate the limitation, we present novel algorithms, whi...

Range searching is a well known problem in the area of geometric data structures. We consider this problem in the context of approximation, where an approximation parameter ε > 0 is provided, and points that are sufficiently close to the range’s boundary may or may not be included. Most prior work on approximating this problem has focused on the case of relative errors, in which it is assumed t...

One aspect of evolutionary computing as a method of data mining, is its intrinsic ability to drive model selection according to a mixed set of criteria. Based on natural selection, evolutionary computing utilizes evaluation of candidate solutions according to a ftness criteria that ~xfight or might not share the exact same implementation as the metric used to measure the performance of the sele...

gully erosion is one of the most complicated and destructive forms of water erosion. in order to prevent this erosion, the important factors advancing gully head must be recognized. nowadays, several models have been proposed in measuring gully head advancement and identifying the severity of erosion. these models must be calibrated for each country to see whether they are applicable or not. so...

The approximation of the general hypergeometric function H(a;b;x) = pFq(a;b;x) to any specified absolute error bound is shown to be solvable. In other words, we provide an algorithm that is uniform in the hypergeometric parameters a = (a1, . . . , ap),b = (b1, . . . , bq). An explicit bound for the complexity of our algorithm is given when the input numbers are rational. We further address the ...

A closed-form expression and an upper bound are obtained for the mean absolute error of the unbiased estimator of a probability in inverse binomial sampling. The results given permit the estimation of an arbitrary probability with a prescribed level of the normalized mean absolute error.

This study evaluated measures for making comparisons of errors across time series. We analyzed 90 annual and 101 quarterly economic time series. We judged error measures on reliability, construct validity, sensitivity to small changes, protection against outliers, and their relationship to decision making. The results lead us to recommend the Geometric Mean of the Relative Absolute Error (GMRAE...

We study in this paper the consequences of using the Mean Absolute Percentage Error (MAPE) as a measure of quality for regression models. We show that finding the best model under the MAPE is equivalent to doing weighted Mean Absolute Error (MAE) regression. We show that universal consistency of Empirical Risk Minimization remains possible using the MAPE instead of the MAE.