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Drift (data Science)
In predictive analytics, data science, machine learning and related fields, concept drift or drift is an evolution of data that invalidates the data model. It happens when the statistical properties of the target variable, which the model is trying to predict, change over time in unforeseen ways. This causes problems because the predictions become less accurate as time passes. Drift detection and drift adaptation are of paramount importance in the fields that involve dynamically changing data and data models. Predictive model decay In machine learning and predictive analytics this drift phenomenon is called concept drift. In machine learning, a common element of a data model are the statistical properties, such as probability distribution of the actual data. If they deviate from the statistical properties of the training data set, then the learned predictions may become invalid, if the drift is not addressed. Data configuration decay Another important area is software engineering, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Predictive Analytics
Predictive analytics encompasses a variety of Statistics, statistical techniques from data mining, Predictive modelling, predictive modeling, and machine learning that analyze current and historical facts to make predictions about future or otherwise unknown events. In business, predictive models exploit Pattern detection, patterns found in historical and transactional data to identify risks and opportunities. Models capture relationships among many factors to allow assessment of risk or potential associated with a particular set of conditions, guiding decision-making for candidate transactions. The defining functional effect of these technical approaches is that predictive analytics provides a predictive score (probability) for each individual (customer, employee, healthcare patient, product SKU, vehicle, component, machine, or other organizational unit) in order to determine, inform, or influence organizational processes that pertain across large numbers of individuals, such as ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Prediction
A prediction (Latin ''præ-'', "before," and ''dictum'', "something said") or forecast is a statement about a future event or about future data. Predictions are often, but not always, based upon experience or knowledge of forecasters. There is no universal agreement about the exact difference between "prediction" and " estimation"; different authors and disciplines ascribe different connotations. Future events are necessarily uncertain, so guaranteed accurate information about the future is impossible. Prediction can be useful to assist in making plans about possible developments. Opinion In a non-statistical sense, the term "prediction" is often used to refer to an informed guess or opinion. A prediction of this kind might be informed by a predicting person's abductive reasoning, inductive reasoning, deductive reasoning, and experience; and may be useful—if the predicting person is a knowledgeable person in the field. The Delphi method is a technique for elicitin ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Weka (machine Learning)
The weka, also known as the Māori hen or woodhen (''Gallirallus australis'') is a flightless bird species of the rail family. It is endemic to New Zealand. Some authorities consider it as the only extant member of the genus '' Gallirallus''. Four subspecies are recognized but only two (northern/southern) are supported by genetic evidence. The weka are sturdy brown birds about the size of a chicken. As omnivores, they feed mainly on invertebrates and fruit. Weka usually lay eggs between August and January; both sexes help to incubate. Description Weka are large rails. They are predominantly rich brown mottled with black and grey; the brown shade varies from pale to dark depending on subspecies. The male is the larger sex at in length and in weight. Females measure in length and weigh . The reduced wingspan ranges from . The relatively large, reddish-brown beak is about long, stout and tapered, and used as a weapon. The pointed tail is near-constantly being flicked, a s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
RapidMiner
RapidMiner is a data science platform that analyses the collective impact of an organization's data. It was acquired by Altair Engineering in September 2022. History RapidMiner, formerly known as YALE (Yet Another Learning Environment), was developed by Ralf Klinkenberg, Ingo Mierswa, and Simon Fischer in 2001 at the Artificial Intelligence Unit of the Technical University of Dortmund. Starting in 2006, its development was driven by Rapid-I, a company founded by Ingo Mierswa and Ralf Klinkenberg in the same year. In 2013, the company rebranded from Rapid-I to RapidMiner. Description RapidMiner uses a client/server model with the server offered either on-premises or in public or private cloud infrastructures. RapidMiner provides data mining and machine learning procedures including: Extract, transform, load, data loading and transformation (ETL), data preprocessing and visualization, predictive analytics and statistical modeling, evaluation, and deployment. RapidMiner is written ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Multivariate Distribution
Multivariate is the quality of having multiple variables. It may also refer to: In mathematics * Multivariable calculus * Multivariate function * Multivariate polynomial * Multivariate interpolation * Multivariate optimization In computing * Multivariate cryptography * Multivariate division algorithm * Multivariate optical computing In statistics * Multivariate analysis * Multivariate random variable * Multivariate regression * Multivariate statistics See also * Univariate In mathematics, a univariate object is an expression (mathematics), expression, equation, function (mathematics), function or polynomial involving only one Variable (mathematics), variable. Objects involving more than one variable are ''wikt:multi ... * Bivariate (other) {{disambiguation ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Univariate (statistics)
Univariate is a term commonly used in statistics to describe a type of data which consists of observations on only a single characteristic or attribute. A simple example of univariate data would be the salaries of workers in industry. Like all the other data, univariate data can be visualized using graphs, images or other analysis tools after the data is measured, collected, reported, and analyzed. Data types Some univariate data consists of numbers (such as the height of 65 inches or the weight of 100 pounds), while others are nonnumerical (such as eye colors of brown or blue). Generally, the terms categorical univariate data and numerical univariate data are used to distinguish between these types. Categorical univariate data Categorical univariate data consists of non-numerical observations that may be placed in categories. It includes labels or names used to identify an attribute of each element. Categorical univariate data usually use either nominal or ordinal scale of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Python (programming Language)
Python is a high-level programming language, high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. Python is type system#DYNAMIC, dynamically type-checked and garbage collection (computer science), garbage-collected. It supports multiple programming paradigms, including structured programming, structured (particularly procedural programming, procedural), object-oriented and functional programming. It is often described as a "batteries included" language due to its comprehensive standard library. Guido van Rossum began working on Python in the late 1980s as a successor to the ABC (programming language), ABC programming language, and he first released it in 1991 as Python 0.9.0. Python 2.0 was released in 2000. Python 3.0, released in 2008, was a major revision not completely backward-compatible with earlier versions. Python 2.7.18, released in 2020, was the last release of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Snyk
Snyk Limited is a developer-oriented cybersecurity company, specializing in securing custom developed code, open-source dependencies and cloud infrastructure. It was founded in 2015 out of Tel Aviv and London and is headquartered in Boston. History Snyk was founded in 2015 by Guy Podjarny (Hebrew: גיא פודחרני), Assaf Hefetz (אסף חפץ), and Danny Grander, (דני גרנדר) coming from Unit 8200, a SIGINT unit of the Israel Defense Forces."THE ISRAELI CYBER COMPANY SNYK IS PREPARING FOR AN INITIAL PUBLIC OFFERING" ''Israel Financial Insider'', January 1, 2022 [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Mining
Data mining is the process of extracting and finding patterns in massive data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal of extracting information (with intelligent methods) from a data set and transforming the information into a comprehensible structure for further use. Data mining is the analysis step of the " knowledge discovery in databases" process, or KDD. Aside from the raw analysis step, it also involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating. The term "data mining" is a misnomer because the goal is the extraction of patterns and knowledge from large amounts of data, not the extraction (''mining'') of data itself. It also is a buzzwo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Stream Mining
Data Stream Mining (also known as stream learning) is the process of extracting knowledge structures from continuous, rapid data records. A data stream is an ordered sequence of instances that in many applications of data stream mining can be read only once or a small number of times using limited computing and storage capabilities. In many data stream mining applications, the goal is to predict the class or value of new instances in the data stream given some knowledge about the class membership or values of previous instances in the data stream. Machine learning techniques can be used to learn this prediction task from labeled examples in an automated fashion. Often, concepts from the field of incremental learning are applied to cope with structural changes, on-line learning and real-time demands. In many applications, especially operating within non-stationary environments, the distribution underlying the instances or the rules underlying their labeling may change over time, i. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Biological Processes
Biological processes are those processes that are necessary for an organism to live and that shape its capacities for interacting with its environment. Biological processes are made of many chemical reactions or other events that are involved in the persistence and transformation of life forms. Regulation of biological processes occurs when any process is modulated in its frequency, rate or extent. Biological processes are regulated by many means; examples include the control of gene expression, protein modification or interaction with a protein or substrate molecule. * Homeostasis: regulation of the internal environment to maintain a constant state; for example, sweating to reduce temperature * Organization: being structurally composed of one or more cells – the basic units of life * Metabolism: transformation of energy by converting chemicals and energy into cellular components (anabolism) and decomposing organic matter ( catabolism). Living things require energy to mai ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Socioeconomic
Economics () is a behavioral science that studies the Production (economics), production, distribution (economics), distribution, and Consumption (economics), consumption of goods and services. Economics focuses on the behaviour and interactions of Agent (economics), economic agents and how economy, economies work. Microeconomics analyses what is viewed as basic elements within economy, economies, including individual agents and market (economics), markets, their interactions, and the outcomes of interactions. Individual agents may include, for example, households, firms, buyers, and sellers. Macroeconomics analyses economies as systems where production, distribution, consumption, savings, and Expenditure, investment expenditure interact; and the factors of production affecting them, such as: Labour (human activity), labour, Capital (economics), capital, Land (economics), land, and Entrepreneurship, enterprise, inflation, economic growth, and public policies that impact gloss ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
