Categorical distributionIn probability theory and statistics, a categorical distribution (also called a generalized Bernoulli distribution, multinoulli distribution) is a discrete probability distribution that describes the possible results of a random variable that can take on one of K possible categories, with the probability of each category separately specified. There is no innate underlying ordering of these outcomes, but numerical labels are often attached for convenience in describing the distribution, (e.g. 1 to K).
Bayes estimatorIn estimation theory and decision theory, a Bayes estimator or a Bayes action is an estimator or decision rule that minimizes the posterior expected value of a loss function (i.e., the posterior expected loss). Equivalently, it maximizes the posterior expectation of a utility function. An alternative way of formulating an estimator within Bayesian statistics is maximum a posteriori estimation. Suppose an unknown parameter is known to have a prior distribution .
Mid-rangeIn statistics, the mid-range or mid-extreme is a measure of central tendency of a sample defined as the arithmetic mean of the maximum and minimum values of the data set: The mid-range is closely related to the range, a measure of statistical dispersion defined as the difference between maximum and minimum values. The two measures are complementary in sense that if one knows the mid-range and the range, one can find the sample maximum and minimum values.
Griswold v. ConnecticutGriswold v. Connecticut, 381 U.S. 479 (1965), was a landmark decision of the U.S. Supreme Court in which the Court ruled that the Constitution of the United States protects the liberty of married couples to buy and use contraceptives without government restriction. The case involved a Connecticut "Comstock law" that prohibited any person from using "any drug, medicinal article or instrument for the purpose of preventing conception". The court held that the statute was unconstitutional, and that its effect was "to deny disadvantaged citizens .
Privacy settingsPrivacy settings are "the part of a social networking website, internet browser, piece of software, etc. that allows you to control who sees information about you". With the growing prevalence of social networking services, opportunities for privacy exposures also grow. Privacy settings allow a person to control what information is shared on these platforms. Many social networking services (SNS) such as Facebook, have default privacy settings that leave users more prone to sharing personal information.
Data re-identificationData re-identification or de-anonymization is the practice of matching anonymous data (also known as de-identified data) with publicly available information, or auxiliary data, in order to discover the person the data belong to. This is a concern because companies with privacy policies, health care providers, and financial institutions may release the data they collect after the data has gone through the de-identification process.
Evaluation of binary classifiersThe evaluation of binary classifiers compares two methods of assigning a binary attribute, one of which is usually a standard method and the other is being investigated. There are many metrics that can be used to measure the performance of a classifier or predictor; different fields have different preferences for specific metrics due to different goals. For example, in medicine sensitivity and specificity are often used, while in computer science precision and recall are preferred.
Human Rights Act 1998The Human Rights Act 1998 (c. 42) is an Act of Parliament of the United Kingdom which received royal assent on 9 November 1998, and came into force on 2 October 2000. Its aim was to incorporate into UK law the rights contained in the European Convention on Human Rights. The Act makes a remedy for breach of a Convention right available in UK courts, without the need to go to the European Court of Human Rights (ECHR) in Strasbourg.
PseudonymizationPseudonymization is a data management and de-identification procedure by which personally identifiable information fields within a data record are replaced by one or more artificial identifiers, or pseudonyms. A single pseudonym for each replaced field or collection of replaced fields makes the data record less identifiable while remaining suitable for data analysis and data processing. Pseudonymization (or pseudonymisation, the spelling under European guidelines) is one way to comply with the European Union's new General Data Protection Regulation (GDPR) demands for secure data storage of personal information.
