Persian catThe Persian cat, also known as the Persian longhair, is a long-haired breed of cat characterized by a round face and short muzzle. The first documented ancestors of Persian cats might have been imported into Italy from Khorasan as early as around 1620, however this has not been proven. Instead there is stronger evidence for a longhaired cat breed being exported from Afghanistan and Iran from the 19th century onwards. Widely recognized by cat fancy since the late 19th century, Persian cats were first adopted by the British, and later by American breeders after World War II.
Dog breedA dog breed is a particular type of dog that was purposefully bred by humans to perform specific tasks, such as herding, hunting, and guarding. Dogs are the most variable mammal on Earth, with artificial selection producing around 450 globally recognized breeds. These breeds possess distinct traits related to morphology, which include body size, skull shape, tail phenotype, fur type, body shape, and coat colour. Their behavioral traits include guarding, herding, and hunting, and personality traits such as hyper-social behavior, boldness, and aggression.
Sphynx catThe Sphynx cat (pronounced , ˈsfɪŋks) also known as the Canadian Sphynx, is a breed of cat known for its lack of fur. Hairlessness in cats is a naturally occurring genetic mutation, and the Sphynx was developed through selective breeding of these animals, starting in the 1960s. According to breed standards, the skin should have the texture of chamois leather, as it has fine hairs, or the cat may be completely hairless. Whiskers may be present, either whole or broken, or may be totally absent.
Medical recordThe terms medical record, health record and medical chart are used somewhat interchangeably to describe the systematic documentation of a single patient's medical history and care across time within one particular health care provider's jurisdiction. A medical record includes a variety of types of "notes" entered over time by healthcare professionals, recording observations and administration of drugs and therapies, orders for the administration of drugs and therapies, test results, X-rays, reports, etc.
Electronic health recordAn electronic health record (EHR) is the systematized collection of patient and population electronically stored health information in a digital format. These records can be shared across different health care settings. Records are shared through network-connected, enterprise-wide information systems or other information networks and exchanges. EHRs may include a range of data, including demographics, medical history, medication and allergies, immunization status, laboratory test results, radiology images, vital signs, personal statistics like age and weight, and billing information.
Loss functionIn mathematical optimization and decision theory, a loss function or cost function (sometimes also called an error function) is a function that maps an event or values of one or more variables onto a real number intuitively representing some "cost" associated with the event. An optimization problem seeks to minimize a loss function. An objective function is either a loss function or its opposite (in specific domains, variously called a reward function, a profit function, a utility function, a fitness function, etc.
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.
Normal distributionIn statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable. The general form of its probability density function is The parameter is the mean or expectation of the distribution (and also its median and mode), while the parameter is its standard deviation. The variance of the distribution is . A random variable with a Gaussian distribution is said to be normally distributed, and is called a normal deviate.
Bias–variance tradeoffIn statistics and machine learning, the bias–variance tradeoff is the property of a model that the variance of the parameter estimated across samples can be reduced by increasing the bias in the estimated parameters. The bias–variance dilemma or bias–variance problem is the conflict in trying to simultaneously minimize these two sources of error that prevent supervised learning algorithms from generalizing beyond their training set: The bias error is an error from erroneous assumptions in the learning algorithm.
Naive Bayes classifierIn statistics, naive Bayes classifiers are a family of simple "probabilistic classifiers" based on applying Bayes' theorem with strong (naive) independence assumptions between the features (see Bayes classifier). They are among the simplest Bayesian network models, but coupled with kernel density estimation, they can achieve high accuracy levels. Naive Bayes classifiers are highly scalable, requiring a number of parameters linear in the number of variables (features/predictors) in a learning problem.
Stable distributionIn probability theory, a distribution is said to be stable if a linear combination of two independent random variables with this distribution has the same distribution, up to location and scale parameters. A random variable is said to be stable if its distribution is stable. The stable distribution family is also sometimes referred to as the Lévy alpha-stable distribution, after Paul Lévy, the first mathematician to have studied it. Of the four parameters defining the family, most attention has been focused on the stability parameter, (see panel).
Fuzzy logicFuzzy logic is a form of many-valued logic in which the truth value of variables may be any real number between 0 and 1. It is employed to handle the concept of partial truth, where the truth value may range between completely true and completely false. By contrast, in Boolean logic, the truth values of variables may only be the integer values 0 or 1. The term fuzzy logic was introduced with the 1965 proposal of fuzzy set theory by Iranian Azerbaijani mathematician Lotfi Zadeh.
