Online machine learningIn computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update the best predictor for future data at each step, as opposed to batch learning techniques which generate the best predictor by learning on the entire training data set at once. Online learning is a common technique used in areas of machine learning where it is computationally infeasible to train over the entire dataset, requiring the need of out-of-core algorithms.
Stability (learning theory)Stability, also known as algorithmic stability, is a notion in computational learning theory of how a machine learning algorithm output is changed with small perturbations to its inputs. A stable learning algorithm is one for which the prediction does not change much when the training data is modified slightly. For instance, consider a machine learning algorithm that is being trained to recognize handwritten letters of the alphabet, using 1000 examples of handwritten letters and their labels ("A" to "Z") as a training set.
Anomaly detectionIn data analysis, anomaly detection (also referred to as outlier detection and sometimes as novelty detection) is generally understood to be the identification of rare items, events or observations which deviate significantly from the majority of the data and do not conform to a well defined notion of normal behaviour. Such examples may arouse suspicions of being generated by a different mechanism, or appear inconsistent with the remainder of that set of data.
Text miningText mining, text data mining (TDM) or text analytics is the process of deriving high-quality information from text. It involves "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources." Written resources may include websites, books, emails, reviews, and articles. High-quality information is typically obtained by devising patterns and trends by means such as statistical pattern learning. According to Hotho et al.
Written languageA written language is the representation of a language by means of writing. This involves the use of visual symbols, known as graphemes, to represent linguistic units such as phonemes, syllables, morphemes, or words. However, it is important to note that written language is not merely spoken or signed language written down, though it can approximate that. Instead, it is a separate system with its own norms, structures, and stylistic conventions, and it often evolves differently than its corresponding spoken or signed language.
WritingWriting is a cognitive and social activity involving neuropsychological and physical processes and the use of writing systems to structure and translate human thoughts into persistent representations of human language. A system of writing relies on many of the same semantic structures as the language it represents, such as lexicon and syntax, with the added dependency of a system of symbols representing that language's phonology and morphology. Nevertheless, written language may take on characteristics distinctive from any available in spoken language.
