Classical liberalismClassical liberalism is a political tradition and a branch of liberalism that advocates free market and laissez-faire economics; and civil liberties under the rule of law, with special emphasis on individual autonomy, limited government, economic freedom, political freedom and freedom of speech. Classical liberalism, contrary to liberal branches like social liberalism, looks more negatively on social policies, taxation and the state involvement in the lives of individuals, and it advocates deregulation.
Work–life interfaceWork–life interface is the intersection of work and personal life. There are many aspects of one's personal life that can intersect with work, including family, leisure, and health. Work–life interface is bidirectional; for instance, work can interfere with private life, and private life can interfere with work. This interface can be adverse in nature (e.g., work–life conflict) or can be beneficial (e.g., work–life enrichment) in nature. Recent research has shown that the work–life interface has become more boundary-less, especially for technology-enabled workers.
Classical antiquityClassical antiquity, also known as the classical era, classical period, classical age, or simply antiquity, is the period of cultural history between the 8th century BC and the 8th century AD centered on the Mediterranean Sea, comprising the interlocking civilizations of ancient Greece and ancient Rome known as the Greco-Roman world. It is the period in which both Greek and Roman societies flourished and wielded huge influence throughout much of Europe, North Africa, and West Asia.
Probabilistic logic networkA probabilistic logic network (PLN) is a conceptual, mathematical and computational approach to uncertain inference; inspired by logic programming, but using probabilities in place of crisp (true/false) truth values, and fractional uncertainty in place of crisp known/unknown values. In order to carry out effective reasoning in real-world circumstances, artificial intelligence software must robustly handle uncertainty.
Central tendencyIn statistics, a central tendency (or measure of central tendency) is a central or typical value for a probability distribution. Colloquially, measures of central tendency are often called averages. The term central tendency dates from the late 1920s. The most common measures of central tendency are the arithmetic mean, the median, and the mode. A middle tendency can be calculated for either a finite set of values or for a theoretical distribution, such as the normal distribution.
Classical republicanismClassical republicanism, also known as civic republicanism or civic humanism, is a form of republicanism developed in the Renaissance inspired by the governmental forms and writings of classical antiquity, especially such classical writers as Aristotle, Polybius, and Cicero. Classical republicanism is built around concepts such as liberty as non-domination, self-government, rule of law, property-based personality, anti-corruption, abolition of monarchy, civics, civil society, common good, civic virtue, popular sovereignty, patriotism and mixed government.
Classical logicClassical logic (or standard logic or Frege-Russell logic) is the intensively studied and most widely used class of deductive logic. Classical logic has had much influence on analytic philosophy. Each logical system in this class shares characteristic properties: Law of excluded middle and double negation elimination Law of noncontradiction, and the principle of explosion Monotonicity of entailment and idempotency of entailment Commutativity of conjunction De Morgan duality: every logical operator is dual to another While not entailed by the preceding conditions, contemporary discussions of classical logic normally only include propositional and first-order logics.
Error detection and correctionIn information theory and coding theory with applications in computer science and telecommunication, error detection and correction (EDAC) or error control are techniques that enable reliable delivery of digital data over unreliable communication channels. Many communication channels are subject to channel noise, and thus errors may be introduced during transmission from the source to a receiver. Error detection techniques allow detecting such errors, while error correction enables reconstruction of the original data in many cases.
Prior probabilityA prior probability distribution of an uncertain quantity, often simply called the prior, is its assumed probability distribution before some evidence is taken into account. For example, the prior could be the probability distribution representing the relative proportions of voters who will vote for a particular politician in a future election. The unknown quantity may be a parameter of the model or a latent variable rather than an observable variable.
Inverse problemAn inverse problem in science is the process of calculating from a set of observations the causal factors that produced them: for example, calculating an image in X-ray computed tomography, source reconstruction in acoustics, or calculating the density of the Earth from measurements of its gravity field. It is called an inverse problem because it starts with the effects and then calculates the causes. It is the inverse of a forward problem, which starts with the causes and then calculates the effects.
Decision theoryDecision theory (or the theory of choice; not to be confused with choice theory) is a branch of applied probability theory and analytic philosophy concerned with the theory of making decisions based on assigning probabilities to various factors and assigning numerical consequences to the outcome. There are three branches of decision theory: Normative decision theory: Concerned with the identification of optimal decisions, where optimality is often determined by considering an ideal decision-maker who is able to calculate with perfect accuracy and is in some sense fully rational.
Tf–idfIn information retrieval, tf–idf (also TF*IDF, TFIDF, TF–IDF, or Tf–idf), short for term frequency–inverse document frequency, is a numerical statistic that is intended to reflect how important a word is to a document in a collection or corpus. It is often used as a weighting factor in searches of information retrieval, text mining, and user modeling. The tf–idf value increases proportionally to the number of times a word appears in the document and is offset by the number of documents in the corpus that contain the word, which helps to adjust for the fact that some words appear more frequently in general.
