We propose and evaluate explicit tests of the null hypothesis of no difference in the accuracy of two competing forecasts. In contrast to previously developed tests, a wide variety of accuracy measures can be used (in particular, the loss function need not be quadratic, and need not even

improved accuracy of the data processing software and reliable accuracy measures to reduce the need for human involvement in error correction and make human review more efficient. Here, we describe one step toward that goal: a base-calling program for automated sequencer traces, phred, with improved

1 This paper looks into the issue of evaluating forecast accuracy measures. In the theoretical direction, for comparing two forecasters, only when the errors are stochastically ordered, the ranking of the forecasts is basically independent of the form of the chosen measure. We propose wellmotivated

the number of required traces compared to a brute-force, all-to-all approach by three orders of magnitude without a significant loss in accuracy. They include the use of BGP routing tables to focus the measurements, exploiting properties of IP routing to eliminate redundant measurements, better alias

DCT of blocks of 8x8 pixels. 100 random blocks of 8x8 pixels are transformed by forward DCT and then recovered by inverse DCT. Accuracy measured as percentage of correctly recovered pixels. ##### ## ## ## ## ## ## ## # # # # # ################# ################ ######## Minimizing Floating Point

), a Ø 2 -test (CHI), and term strength (TS). We found IG and CHI most effective in our experiments. Using IG thresholding with a knearest neighbor classifier on the Reuters corpus, removal of up to 98% removal of unique terms actually yielded an improved classification accuracy (measured by average

Abstract — The selection of the best classification algorithm for a given dataset is a very widespread problem. It is also a complex one, in the sense it requires to make several important methodological choices. Among them, in this work we focus on the measure used to assess the classification

), and is controlled by the subject. A series of studies using both reaction time and accuracy measures is presented, which traces these concepts in the form of automatic detection and controlled, search through the areas of detection, search, and attention. Results in these areas are shown to arise from common

DMOZ is the largest, most comprehensive human edited directory of the web. –> 718,201 hierarchical categories. – 4,815,303 validated entries in 79 languages – Available in RDF downloadThe DataWhat is classification? A process where, given an uncategorized web document, predict the DMOZ category. – Given an input vector x assign it to one of K discrete classes. – Parametric or nonparametric; unsupervised, semisupervised or supervised learningPopular Methods

At PoliticalForecasting.com, better known as the Pollyvote, the authors combine forecasts from four sources: election polls, a panel of American political experts, the Iowa Electronic Market, and quantitative models. The day before the election, Polly predicted that the Republican ticket’s share of the two-party vote would be 47.0%. The outcome was close at 46.6 % (as of the end of November). In his Hot New Research column in this issue, Paul Goodwin discusses the benefits of combining forecasts. The success of the Pollyvote should further enhance interest is this approach to forecasting.