Logistic regressionIn statistics, the logistic model (or logit model) is a statistical model that models the probability of an event taking place by having the log-odds for the event be a linear combination of one or more independent variables. In regression analysis, logistic regression (or logit regression) is estimating the parameters of a logistic model (the coefficients in the linear combination).
Real propertyIn English common law, real property, real estate, immovable property or, solely in the US and Canada, realty, is land which is the property of some person and all structures (also called improvements or fixtures) integrated with or affixed to the land, including crops, buildings, machinery, wells, dams, ponds, mines, canals, roads, and other things. The term is historic, arising from the now-discontinued form of action, which distinguished between real property disputes and personal property disputes.
Criminal procedureCriminal procedure is the adjudication process of the criminal law. While criminal procedure differs dramatically by jurisdiction, the process generally begins with a formal criminal charge with the person on trial either being free on bail or incarcerated, and results in the conviction or acquittal of the defendant. Criminal procedure can be either in form of inquisitorial or adversarial criminal procedure.
Civil procedureCivil procedure is the body of law that sets out the rules and standards that courts follow when adjudicating civil lawsuits (as opposed to procedures in criminal law matters). These rules govern how a lawsuit or case may be commenced; what kind of service of process (if any) is required; the types of pleadings or statements of case, motions or applications, and orders allowed in civil cases; the timing and manner of depositions and discovery or disclosure; the conduct of trials; the process for judgment; the process for post-trial procedures; various available remedies; and how the courts and clerks must function.
Ridge regressionRidge regression is a method of estimating the coefficients of multiple-regression models in scenarios where the independent variables are highly correlated. It has been used in many fields including econometrics, chemistry, and engineering. Also known as Tikhonov regularization, named for Andrey Tikhonov, it is a method of regularization of ill-posed problems. It is particularly useful to mitigate the problem of multicollinearity in linear regression, which commonly occurs in models with large numbers of parameters.
Ordinal regressionIn statistics, ordinal regression, also called ordinal classification, is a type of regression analysis used for predicting an ordinal variable, i.e. a variable whose value exists on an arbitrary scale where only the relative ordering between different values is significant. It can be considered an intermediate problem between regression and classification. Examples of ordinal regression are ordered logit and ordered probit.
Logical disjunctionIn logic, disjunction, also known as logical disjunction or logical or or logical addition or inclusive disjunction , is a logical connective typically notated as and read aloud as "or". For instance, the English language sentence "it is sunny or it is warm" can be represented in logic using the disjunctive formula , assuming that abbreviates "it is sunny" and abbreviates "it is warm". In classical logic, disjunction is given a truth functional semantics according to which a formula is true unless both and are false.
Logical conjunctionIn logic, mathematics and linguistics, and () is the truth-functional operator of conjunction or logical conjunction. The logical connective of this operator is typically represented as or or (prefix) or or in which is the most modern and widely used. The and of a set of operands is true if and only if all of its operands are true, i.e., is true if and only if is true and is true. An operand of a conjunction is a conjunct.
Ensemble learningIn statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from any of the constituent learning algorithms alone. Unlike a statistical ensemble in statistical mechanics, which is usually infinite, a machine learning ensemble consists of only a concrete finite set of alternative models, but typically allows for much more flexible structure to exist among those alternatives.
Model theoryIn mathematical logic, model theory is the study of the relationship between formal theories (a collection of sentences in a formal language expressing statements about a mathematical structure), and their models (those structures in which the statements of the theory hold). The aspects investigated include the number and size of models of a theory, the relationship of different models to each other, and their interaction with the formal language itself.
