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Open AccessArticle

Channels’ Confirmation and Predictions’ Confirmation: From the Medical Test to the Raven Paradox

Intelligence Engineering and Mathematics Institute, Liaoning Technical University, Fuxin 123000, China
Entropy 2020, 22(4), 384; https://doi.org/10.3390/e22040384
Received: 24 January 2020 / Revised: 25 March 2020 / Accepted: 25 March 2020 / Published: 26 March 2020
(This article belongs to the Special Issue Data Science: Measuring Uncertainties)
After long arguments between positivism and falsificationism, the verification of universal hypotheses was replaced with the confirmation of uncertain major premises. Unfortunately, Hemple proposed the Raven Paradox. Then, Carnap used the increment of logical probability as the confirmation measure. So far, many confirmation measures have been proposed. Measure F proposed by Kemeny and Oppenheim among them possesses symmetries and asymmetries proposed by Elles and Fitelson, monotonicity proposed by Greco et al., and normalizing property suggested by many researchers. Based on the semantic information theory, a measure b* similar to F is derived from the medical test. Like the likelihood ratio, measures b* and F can only indicate the quality of channels or the testing means instead of the quality of probability predictions. Furthermore, it is still not easy to use b*, F, or another measure to clarify the Raven Paradox. For this reason, measure c* similar to the correct rate is derived. Measure c* supports the Nicod Criterion and undermines the Equivalence Condition, and hence, can be used to eliminate the Raven Paradox. An example indicates that measures F and b* are helpful for diagnosing the infection of Novel Coronavirus, whereas most popular confirmation measures are not. Another example reveals that all popular confirmation measures cannot be used to explain that a black raven can confirm “Ravens are black” more strongly than a piece of chalk. Measures F, b*, and c* indicate that the existence of fewer counterexamples is more important than more positive examples’ existence, and hence, are compatible with Popper’s falsification thought. View Full-Text
Keywords: relative entropy; cross-entropy; uncertain reasoning; inductive logic; confirmation measure; semantic information; medical test; raven paradox relative entropy; cross-entropy; uncertain reasoning; inductive logic; confirmation measure; semantic information; medical test; raven paradox
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  • Externally hosted supplementary file 1
    Link: http://survivor99.com/lcg/Table9-12-13NAT.zip .
    Description: The Excel File for Data in Tables 9,12, and 13 is available online at http://survivor99.com/lcg/Table9-12-13NAT.zip . We can test different confirmation measures by changing a, b, c, and d.
MDPI and ACS Style

Lu, C. Channels’ Confirmation and Predictions’ Confirmation: From the Medical Test to the Raven Paradox. Entropy 2020, 22, 384.

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