A Problem for Confirmation Measure Z

2021 ◽  
Author(s):  
Branden Fitelson
Keyword(s):  
Confirmation Measure

scholarly journals Visualization support for the analysis of properties of interestingness measures

2015 ◽  
Vol 63 (1) ◽  
pp. 315-327 ◽  
Author(s):  
R. Susmaga ◽  
I. Szczęch
Keyword(s):  
Real Life ◽  
Scalar Function ◽  
Interestingness Measures ◽  
3 Dimensional ◽  
Confirmation Measure ◽  
Visual Technique ◽  
Confirmation Measures ◽  
The Subject ◽  
Colour Patterns ◽  
Rule Interestingness

Abstract The paper considers a particular group of rule interestingness measures, called Bayesian confirmation measures, which have become the subject of numerous, but often exclusively theoretical studies. To assist and enhance their analysis in real-life situations, where time constraints may impede conducting such time consuming procedures, a visual technique has been introduced and described in this paper. It starts with an exhaustive and non-redundant set of contingency tables, which consists of all possible tables having the same number of observations. These data, originally 4-dimensional, may, owing to an inherent constraint, be effectively represented as a 3-dimensional tetrahedron, while an additional, scalar function of the data (e.g. a confirmation measure) may be rendered using colour. Dedicated analyses of particular colour patterns on this tetrahedron allow to promptly perceive particular properties of the visualized measures. To illustrate the introduced technique, a set of 12 popular confirmation measures has been selected and visualized. Additionally, a set of 9 popular properties has been chosen and the visual interpretations of the measures in terms of the properties have been presented.

Selected group-theoretic aspects of confirmation measure symmetries

2016 ◽  
Vol 346-347 ◽  
pp. 424-441 ◽  
Author(s):  
Robert Susmaga ◽  
Izabela Szczęch
Keyword(s):  
Confirmation Measure

Confirmation Measure

2013 ◽  
Author(s):  
Marcus Lee Johnson ◽  
Gale M. Sinatra
Keyword(s):  
Confirmation Measure

Confirmation Measure

2010 ◽  
Author(s):  
Bo Feng ◽  
Erina L. MacGeorge
Keyword(s):  
Confirmation Measure

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

Entropy ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 384 ◽  
Author(s):  
Chenguang Lu
Keyword(s):  
Semantic Information ◽  
Logical Probability ◽  
Medical Test ◽  
Confirmation Measure ◽  
Confirmation Measures ◽  
Equivalence Condition ◽  
Raven Paradox ◽  
Semantic Information Theory ◽  
Novel Coronavirus

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.

scholarly journals Structure-Activity Relationships of the Imidazolium Compounds as Antibacterials of Staphylococcus aureus and Pseudomonas aeruginosa

2021 ◽  
Vol 22 (15) ◽  
pp. 7997
Author(s):  
Łukasz Pałkowski ◽  
Maciej Karolak ◽  
Jerzy Błaszczyński ◽  
Jerzy Krysiński ◽  
Roman Słowiński
Keyword(s):  
Staphylococcus Aureus ◽  
Pseudomonas Aeruginosa ◽  
Surface Properties ◽  
Decision Rules ◽  
Rank Condition ◽  
Confirmation Measure ◽  
Sar Studies ◽  
Structure Activity ◽  
Decision Attributes ◽  
Sar Analysis

This paper presents the results of structure–activity relationship (SAR) studies of 140 3,3’-(α,ω-dioxaalkan)bis(1-alkylimidazolium) chlorides. In the SAR analysis, the dominance-based rough set approach (DRSA) was used. For analyzed compounds, minimum inhibitory concentration (MIC) against strains of Staphylococcus aureus and Pseudomonas aeruginosa was determined. In order to perform the SAR analysis, a tabular information system was formed, in which tested compounds were described by means of condition attributes, characterizing the structure (substructure parameters and molecular descriptors) and their surface properties, and a decision attribute, classifying compounds with respect to values of MIC. DRSA allows to induce decision rules from data describing the compounds in terms of condition and decision attributes, and to rank condition attributes with respect to relevance using a Bayesian confirmation measure. Decision rules present the most important relationships between structure and surface properties of the compounds on one hand, and their antibacterial activity on the other hand. They also indicate directions of synthesizing more efficient antibacterial compounds. Moreover, the analysis showed differences in the application of various parameters for Gram-positive and Gram-negative strains, respectively.

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