Capsule neural network (CapsNet) (Капсульная нейронная сеть) – A machine learning system that is a type of artificial neural network (ANN) that can be used to better model hierarchical relationships. [94] The approach is an attempt to more closely mimic biological neural organization [95]
Case-Based Reasoning (CBR) (Рассуждения по прецедентам) – is a way to solve a new problem by using solutions to similar problems. It has been formalized to a process consisting of case retrieve, solution reuse, solution revise, and case retention [96].
Categorical data (Категориальные данные) — Features having a discrete set of possible values. For example, consider a categorical feature named house style, which has a discrete set of three possible values: Tudor, ranch, colonial. By representing house style as categorical data, the model can learn the separate impacts of Tudor, ranch, and colonial on house price. Sometimes, values in the discrete set are mutually exclusive, and only one value can be applied to a given example. For example, a car maker categorical feature would probably permit only a single value (Toyota) per example. Other times, more than one value may be applicable. A single car could be painted more than one different color, so a car color categorical feature would likely permit a single example to have multiple values (for example, red and white). Categorical features are sometimes called discrete features. Contrast with numerical data [97].
Center for Technological Competence (Центр технологических компетенций) is an organization that owns the results, tools for conducting fundamental research and platform solutions available to market participants to create applied solutions (products) on their basis. The Technology Competence Center can be a separate organization or be part of an application technology holding company.
Central Processing Units (CPU) (Центральный процессор) is a von Neumann cyclic processor designed to execute complex computer programs.
Centralized control (Централизованное управление) is a process in which control signals are generated in a single control center and transmitted from it to numerous control objects.
Centroid (Центроид) – The center of a cluster as determined by a k-means or k-median algorithm. For instance, if k is 3, then the k-means or k-median algorithm finds 3 centroids.
Centroid-based clustering (Кластеризация на основе центроида) – A category of clustering algorithms that organizes data into nonhierarchical clusters. k-means is the most widely used centroid-based clustering algorithm. Contrast with hierarchical clustering algorithms.
Character format (Формат символов)
Any file format in which information is encoded as characters using only a standard character-encoding scheme. A file written in “character format” contains only those bytes that are prescribed in the encoding scheme as corresponding to the characters in the scheme (e.g., alphabetic and numeric characters, punctuation marks, and spaces). [98]
Chatbot (Чат-бот) is a software application designed to simulate human conversation with users via text or speech. Also referred to as virtual agents, interactive agents, digital assistants, or conversational AI, chatbots are often integrated into applications, websites, or messaging platforms to provide support to users without the use of live human agents. Chatbots originally started out by offering users simple menus of choices, and then evolved to react to particular keywords. “But humans are very inventive in their use of language,” says Forrester’s McKeon-White. Someone looking for a password reset might say they’ve forgotten their access code, or are having problems getting into their account. “There are a lot of different ways to say the same thing,” he says. This is where AI comes in. Natural language processing is a subset of machine learning that enables a system to understand the meaning of written or even spoken language, even where there is a lot of variation in the phrasing. To succeed, a chatbot that relies on AI or machine learning needs first to be trained using a data set. In general, the bigger the training data set, and the narrower the domain, the more accurate and helpful a chatbot will be [99].
Checkpoint (Контрольная точка) — Data that captures the state of the variables of a model at a particular time. Checkpoints enable exporting model weights, as well as performing training across multiple sessions. Checkpoints also enable training to continue past errors (for example, job preemption). Note that the graph itself is not included in a checkpoint.
Chip (Чип) – an electronic microcircuit of arbitrary complexity, made on a semiconductor substrate and placed in a non-separable case or without it, if included in the micro assembly.
Class (Класс) — One of a set of enumerated target values for a label. For example, in a binary classification model that detects spam, the two classes are spam and not spam. In a multi-class classification model that identifies dog breeds, the classes would be poodle, beagle, pug, and so on.
Classification (Классификация). Classification problems use an algorithm to accurately assign test data into specific categories, such as separating apples from oranges. Or, in the real world, supervised learning algorithms can be used to classify spam in a separate folder from your inbox. Linear classifiers, support vector machines, decision trees and random forest are all common types of classification algorithms.
Classification model (Модель классификации) — A type of machine learning model for distinguishing among two or more discrete classes. For example, a natural language processing classification model could determine whether an input sentence was in French, Spanish, or Italian.
Classification threshold (Порог классификации) — A scalar-value criterion that is applied to a model’s predicted score in order to separate the positive class from the negative class. Used when mapping logistic regression results to binary classification.
Clinical Decision Support (CDS) (Поддержка принятия клинических решений) – A clinical decision support system is a health information technology system that is designed to provide physicians and other health professionals with clinical decision support, that is, assistance with clinical decision- making tasks [100].
Clipping (Отсечение) – A technique for handling outliers. Specifically, reducing feature values that are greater than a set maximum value down to that maximum value. Also, increasing feature values that are less than a specific minimum value up to that minimum value. For example, suppose that only a few feature values fall outside the range 40—60. In this case, you could do the following: Clip all values over 60 to be exactly 60. Clip all values under 40 to be exactly 40. In addition to bringing input values within a designated range, clipping can also used to force gradient values within a designated range during training.
Closed dictionary