Publication

Combined 5x2cv $F$-Test for Comparing Supervised Classification Learning Algorithms

1998
Reports

Abstract

Dietterich (1998) reviews five statistical tests proposing the 5x2cv t test for determining whether there is a significant difference between the error rates of two classifiers. In our experiments, we noticed that the 5x2cv t test result may vary depending on factors that should not affect the test and we propose a variant, the combined 5x2cv F test, that combines multiple statistics to get a more robust test. Simulation results show that this combined version of the test has lower Type I error and higher power than 5x2cv proper.

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1998
Reports

Abstract

Official source

Related concepts (31)

Statistical significance

In statistical hypothesis testing, a result has statistical significance when a result at least as "extreme" would be very infrequent if the null hypothesis were true. More precisely, a study's defined significance level, denoted by , is the probability of the study rejecting the null hypothesis, given that the null hypothesis is true; and the p-value of a result, , is the probability of obtaining a result at least as extreme, given that the null hypothesis is true. The result is statistically significant, by the standards of the study, when .

Statistical hypothesis testing

A statistical hypothesis test is a method of statistical inference used to decide whether the data at hand sufficiently support a particular hypothesis. Hypothesis testing allows us to make probabilistic statements about population parameters. While hypothesis testing was popularized early in the 20th century, early forms were used in the 1700s. The first use is credited to John Arbuthnot (1710), followed by Pierre-Simon Laplace (1770s), in analyzing the human sex ratio at birth; see .

Test statistic

A test statistic is a statistic (a quantity derived from the sample) used in statistical hypothesis testing. A hypothesis test is typically specified in terms of a test statistic, considered as a numerical summary of a data-set that reduces the data to one value that can be used to perform the hypothesis test. In general, a test statistic is selected or defined in such a way as to quantify, within observed data, behaviours that would distinguish the null from the alternative hypothesis, where such an alternative is prescribed, or that would characterize the null hypothesis if there is no explicitly stated alternative hypothesis.

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Combined 5x2cv $F$-Test for Comparing Supervised Classification Learning Algorithms

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