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Phi Coefficient
In statistics, the phi coefficient, or mean square contingency coefficient, denoted by ''φ'' or ''r''''φ'', is a measure of association for two binary variables. In machine learning, it is known as the Matthews correlation coefficient (MCC) and used as a measure of the quality of binary (two-class) classifications, introduced by biochemist Brian W. Matthews in 1975. Introduced by Karl Pearson,Cramer, H. (1946). ''Mathematical Methods of Statistics''. Princeton: Princeton University Press, p. 282 (second paragraph). https://archive.org/details/in.ernet.dli.2015.223699 and also known as the ''Yule phi coefficient'' from its introduction by Udny Yule in 1912 this measure is similar to the Pearson correlation coefficient in its interpretation. In meteorology, the phi coefficient, or its square (the latter aligning with M. H. Doolittle's original proposition from 1885), is referred to as the Doolittle Skill Score or the Doolittle Measure of Association. Definition A Pears ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Statistics
Statistics (from German language, German: ', "description of a State (polity), state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the planning of data collection in terms of the design of statistical survey, surveys and experimental design, experiments. When census data (comprising every member of the target population) cannot be collected, statisticians collect data by developing specific experiment designs and survey sample (statistics), samples. Representative sampling assures that inferences and conclusions can reasonably extend from the sample ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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False Positive
A false positive is an error in binary classification in which a test result incorrectly indicates the presence of a condition (such as a disease when the disease is not present), while a false negative is the opposite error, where the test result incorrectly indicates the absence of a condition when it is actually present. These are the two kinds of errors in a binary test, in contrast to the two kinds of correct result (a and a ). They are also known in medicine as a false positive (or false negative) diagnosis, and in statistical classification as a false positive (or false negative) error. In statistical hypothesis testing, the analogous concepts are known as type I and type II errors, where a positive result corresponds to rejecting the null hypothesis, and a negative result corresponds to not rejecting the null hypothesis. The terms are often used interchangeably, but there are differences in detail and interpretation due to the differences between medical testing and sta ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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BioData Mining
''BioData Mining'' is a peer-reviewed open access scientific journal covering data mining methods applied to computational biology and medicine established in 2008. It is published by BioMed Central and the editors-in-chief are Jason H. Moore and Nicholas Tatonetti ( Cedars Sinai Medical Center). Abstracting and indexing The journal is abstracted and indexed in: According to the ''Journal Citation Reports'', the journal has a 2021 impact factor The impact factor (IF) or journal impact factor (JIF) of an academic journal is a type of journal ranking. Journals with higher impact factor values are considered more prestigious or important within their field. The Impact Factor of a journa ... of 4.079. References External links *{{Official website, https://biodatamining.biomedcentral.com/ BioMed Central academic journals Biomedical informatics journals Creative Commons Attribution-licensed journals Academic journals established in 2008 Continuous journals ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Computational Biology
Computational biology refers to the use of techniques in computer science, data analysis, mathematical modeling and Computer simulation, computational simulations to understand biological systems and relationships. An intersection of computer science, biology, and data science, the field also has foundations in applied mathematics, molecular biology, cell biology, chemistry, and genetics. History Bioinformatics, the analysis of informatics processes in biological systems, began in the early 1970s. At this time, research in artificial intelligence was using network models of the human brain in order to generate new algorithms. This use of biological data pushed biological researchers to use computers to evaluate and compare large data sets in their own field. By 1982, researchers shared information via Punched card, punch cards. The amount of data grew exponentially by the end of the 1980s, requiring new computational methods for quickly interpreting relevant information. Per ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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F-score
In statistical analysis of binary classification and information retrieval systems, the F-score or F-measure is a measure of predictive performance. It is calculated from the precision and recall of the test, where the precision is the number of true positive results divided by the number of all samples predicted to be positive, including those not identified correctly, and the recall is the number of true positive results divided by the number of all samples that should have been identified as positive. Precision is also known as positive predictive value, and recall is also known as sensitivity in diagnostic binary classification. The F1 score is the harmonic mean of the precision and recall. It thus symmetrically represents both precision and recall in one metric. The more generic F_\beta score applies additional weights, valuing one of precision or recall more than the other. The highest possible value of an F-score is 1.0, indicating perfect precision and recall, and the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Informedness
Youden's J statistic (also called Youden's index) is a single statistic that captures the performance of a dichotomous diagnostic test. In meteorology, this statistic is referred to as Peirce Skill Score (PSS), Hanssen–Kuipers Discriminant (HKD), or True Skill Statistic (TSS). (Bookmaker) Informedness is its generalization to the multiclass case and estimates the probability of an informed decision. Definition Youden's ''J'' statistic is : J = \text + \text -1=\text_1 + \text_0 -1 with the two right-hand quantities being sensitivity and specificity. Thus the expanded formula is: :J = \frac+\frac-1 = \frac In this equation, TP is the number of true positives, TN the number of true negatives, FP the number of false positives and FN the number of false negatives. The index was suggested by W. J. Youden in 1950 as a way of summarising the performance of a diagnostic test; however, the formula was earlier published in ''Science'' by C. S. Peirce in 1884. Its value range ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Markedness
In linguistics and social sciences, markedness is the state of standing out as nontypical or divergent as opposed to regular or common. In a marked–unmarked relation, one term of an opposition is the broader, dominant one. The dominant default or minimum-effort form is known as ''unmarked''; the other, secondary one is ''marked''. In other words, markedness involves the characterization of a "normal" linguistic unit against one or more of its possible "irregular" forms. In linguistics, markedness can apply to, among others, phonological, grammatical, and semantic oppositions, defining them in terms of marked and unmarked oppositions, such as ''honest'' (unmarked) vs. ''dishonest'' (marked). Marking may be purely semantic, or may be realized as extra morphology. The term derives from the marking of a grammatical role with a suffix or another element, and has been extended to situations where there is no morphological distinction. In social sciences more broadly, markedness ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Informedness
Youden's J statistic (also called Youden's index) is a single statistic that captures the performance of a dichotomous diagnostic test. In meteorology, this statistic is referred to as Peirce Skill Score (PSS), Hanssen–Kuipers Discriminant (HKD), or True Skill Statistic (TSS). (Bookmaker) Informedness is its generalization to the multiclass case and estimates the probability of an informed decision. Definition Youden's ''J'' statistic is : J = \text + \text -1=\text_1 + \text_0 -1 with the two right-hand quantities being sensitivity and specificity. Thus the expanded formula is: :J = \frac+\frac-1 = \frac In this equation, TP is the number of true positives, TN the number of true negatives, FP the number of false positives and FN the number of false negatives. The index was suggested by W. J. Youden in 1950 as a way of summarising the performance of a diagnostic test; however, the formula was earlier published in ''Science'' by C. S. Peirce in 1884. Its value range ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Youden's J Statistic
Youden's J statistic (also called Youden's index) is a single statistic that captures the performance of a dichotomy, dichotomous diagnostic test. In meteorology, this statistic is referred to as Peirce Skill Score (PSS), Hanssen–Kuipers Discriminant (HKD), or True Skill Statistic (TSS). (Bookmaker) Informedness is its generalization to the multiclass case and estimates the probability of an Decision-making, informed decision. Definition Youden's ''J'' statistic is : J = \text + \text -1=\text_1 + \text_0 -1 with the two right-hand quantities being sensitivity and specificity. Thus the expanded formula is: :J = \frac+\frac-1 = \frac In this equation, TP is the number of true positives, TN the number of true negatives, FP the number of false positives and FN the number of false negatives. The index was suggested by William J. Youden, W. J. Youden in 1950 as a way of summarising the performance of a diagnostic test; however, the formula was earlier published in ''Scienc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Markedness
In linguistics and social sciences, markedness is the state of standing out as nontypical or divergent as opposed to regular or common. In a marked–unmarked relation, one term of an opposition is the broader, dominant one. The dominant default or minimum-effort form is known as ''unmarked''; the other, secondary one is ''marked''. In other words, markedness involves the characterization of a "normal" linguistic unit against one or more of its possible "irregular" forms. In linguistics, markedness can apply to, among others, phonological, grammatical, and semantic oppositions, defining them in terms of marked and unmarked oppositions, such as ''honest'' (unmarked) vs. ''dishonest'' (marked). Marking may be purely semantic, or may be realized as extra morphology. The term derives from the marking of a grammatical role with a suffix or another element, and has been extended to situations where there is no morphological distinction. In social sciences more broadly, markedness ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Dual (mathematics)
In mathematics, a duality translates concepts, theorems or mathematical structures into other concepts, theorems or structures in a Injective function, one-to-one fashion, often (but not always) by means of an Involution (mathematics), involution operation: if the dual of is , then the dual of is . In other cases the dual of the dual – the double dual or bidual – is not necessarily identical to the original (also called ''primal''). Such involutions sometimes have fixed point (mathematics), fixed points, so that the dual of is itself. For example, Desargues' theorem is self-dual in this sense under the ''standard duality (projective geometry), duality in projective geometry''. In mathematical contexts, ''duality'' has numerous meanings. It has been described as "a very pervasive and important concept in (modern) mathematics" and "an important general theme that has manifestations in almost every area of mathematics". Many mathematical dualities between objects of two type ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Regression Coefficient
In statistics, linear regression is a model that estimates the relationship between a scalar response (dependent variable) and one or more explanatory variables (regressor or independent variable). A model with exactly one explanatory variable is a ''simple linear regression''; a model with two or more explanatory variables is a multiple linear regression. This term is distinct from multivariate linear regression, which predicts multiple correlated dependent variables rather than a single dependent variable. In linear regression, the relationships are modeled using linear predictor functions whose unknown model parameters are estimated from the data. Most commonly, the conditional mean of the response given the values of the explanatory variables (or predictors) is assumed to be an affine function of those values; less commonly, the conditional median or some other quantile is used. Like all forms of regression analysis, linear regression focuses on the conditional probab ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |