Conditional random fieldConditional random fields (CRFs) are a class of statistical modeling methods often applied in pattern recognition and machine learning and used for structured prediction. Whereas a classifier predicts a label for a single sample without considering "neighbouring" samples, a CRF can take context into account. To do so, the predictions are modelled as a graphical model, which represents the presence of dependencies between the predictions. What kind of graph is used depends on the application.
Gender roleA gender role, also known as a sex role, is a social role encompassing a range of behaviors and attitudes that are generally considered acceptable, appropriate, or desirable for a person based on that person's sex. Gender roles are usually centered on conceptions of masculinity and femininity, although there are exceptions and variations. The specifics regarding these gendered expectations may vary among cultures, while other characteristics may be common throughout a range of cultures.
Discriminative modelDiscriminative models, also referred to as conditional models, are a class of logistical models used for classification or regression. They distinguish decision boundaries through observed data, such as pass/fail, win/lose, alive/dead or healthy/sick. Typical discriminative models include logistic regression (LR), conditional random fields (CRFs) (specified over an undirected graph), decision trees, and many others. Typical generative model approaches include naive Bayes classifiers, Gaussian mixture models, variational autoencoders, generative adversarial networks and others.
Generative modelIn statistical classification, two main approaches are called the generative approach and the discriminative approach. These compute classifiers by different approaches, differing in the degree of statistical modelling. Terminology is inconsistent, but three major types can be distinguished, following : A generative model is a statistical model of the joint probability distribution on given observable variable X and target variable Y; A discriminative model is a model of the conditional probability of the target Y, given an observation x; and Classifiers computed without using a probability model are also referred to loosely as "discriminative".
Markov random fieldIn the domain of physics and probability, a Markov random field (MRF), Markov network or undirected graphical model is a set of random variables having a Markov property described by an undirected graph. In other words, a random field is said to be a Markov random field if it satisfies Markov properties. The concept originates from the Sherrington–Kirkpatrick model. A Markov network or MRF is similar to a Bayesian network in its representation of dependencies; the differences being that Bayesian networks are directed and acyclic, whereas Markov networks are undirected and may be cyclic.
RoleA role (also rôle or social role) is a set of connected behaviors, rights, obligations, beliefs, and norms as conceptualized by people in a social situation. It is an expected or free or continuously changing behavior and may have a given individual social status or social position. It is vital to both functionalist and interactionist understandings of society. Social role theory posits the following about social behavior: The division of labour in society takes the form of the interaction among heterogeneous specialized positions, we call roles.
Conditional probabilityIn probability theory, conditional probability is a measure of the probability of an event occurring, given that another event (by assumption, presumption, assertion or evidence) has already occurred. This particular method relies on event B occurring with some sort of relationship with another event A. In this event, the event B can be analyzed by a conditional probability with respect to A. If the event of interest is A and the event B is known or assumed to have occurred, "the conditional probability of A given B", or "the probability of A under the condition B", is usually written as P(AB) or occasionally P_B(A).
Conditional probability distributionIn probability theory and statistics, given two jointly distributed random variables and , the conditional probability distribution of given is the probability distribution of when is known to be a particular value; in some cases the conditional probabilities may be expressed as functions containing the unspecified value of as a parameter. When both and are categorical variables, a conditional probability table is typically used to represent the conditional probability.
Social workSocial work (SW) is an academic discipline and practice-based profession concerned with meeting the basic needs of individuals, families, groups, communities, and society as a whole to enhance their individual and collective well-being. Social work practice draws from areas, such as psychology, sociology, health, political science, community development, law, and economics to engage with systems and policies, conduct assessments, develop interventions, and enhance social functioning and responsibility.
Social construction of genderThe social construction of gender is a theory in sociology about the manifestation of cultural origins, mechanisms, and corollaries of gender perception and expression in the context of interpersonal and group social interaction. Specifically, the social construction of gender theory stipulates that gender roles are an achieved "status" in a social environment, which implicitly and explicitly categorize people and therefore motivate social behaviors.
