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Predictive Analytics
Predictive analytics encompasses a variety of statistical techniques from data mining, 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 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 in marketing, credit risk assessment, fraud detecti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistics
Statistics (from German language, German: ''wikt:Statistik#German, Statistik'', "description of a State (polity), state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the planning of data collection in terms of the design of statistical survey, surveys and experimental design, experiments.Dodge, Y. (2006) ''The Oxford Dictionary of Statistical Terms'', Oxford University Press. When census data cannot be collected, statisticians collect data by developing specific experiment designs and survey sample (statistics), samples. Representative sampling as ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Massive Parallel Processing
Massively parallel is the term for using a large number of computer processors (or separate computers) to simultaneously perform a set of coordinated computations in parallel. GPUs are massively parallel architecture with tens of thousands of threads. One approach is grid computing, where the processing power of many computers in distributed, diverse administrative domains is opportunistically used whenever a computer is available.''Grid computing: experiment management, tool integration, and scientific workflows'' by Radu Prodan, Thomas Fahringer 2007 pages 1–4 An example is BOINC, a volunteer-based, opportunistic grid system, whereby the grid provides power only on a best effort basis.''Parallel and Distributed Computational Intelligence'' by Francisco Fernández de Vega 2010 pages 65–68 Another approach is grouping many processors in close proximity to each other, as in a computer cluster. In such a centralized system the speed and flexibility of the interconnect b ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Underwrite
Underwriting (UW) services are provided by some large financial institutions, such as banks, insurance companies and investment houses, whereby they guarantee payment in case of damage or financial loss and accept the financial risk for liability arising from such guarantee. An underwriting arrangement may be created in a number of situations including insurance, issues of security in a public offering, and bank lending, among others. The person or institution that agrees to sell a minimum number of securities of the company for commission is called the underwriter. History The term "underwriting" derives from the Lloyd's of London insurance market. Financial backers (or risk takers), who would accept some of the risk on a given venture (historically a sea voyage with associated risks of shipwreck) in exchange for a premium, would literally write their names under the risk information that was written on a Lloyd's slip created for this purpose. Securities underwriting In the f ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
List Of National Legal Systems
The contemporary national legal systems are generally based on one of four basic systems: civil law, common law, statutory law, religious law or combinations of these. However, the legal system of each country is shaped by its unique history and so incorporates individual variations. The science that studies law at the level of legal systems is called comparative law. Both ''civil'' (also known as ''Roman'') and ''common'' law systems can be considered the most widespread in the world: civil law because it is the most widespread by landmass and by population overall, and common law because it is employed by the greatest number of people compared to any single civil law system. Civil law The source of law that is recognized as authoritative is codifications in a constitution or statute passed by legislature, to amend a code. While the concept of codification dates back to the Code of Hammurabi in Babylon ca. 1790 BC, civil law systems derive from the Roman Empire and, more p ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Parkinson's Disease
Parkinson's disease (PD), or simply Parkinson's, is a long-term degenerative disorder of the central nervous system that mainly affects the motor system. The symptoms usually emerge slowly, and as the disease worsens, non-motor symptoms become more common. The most obvious early symptoms are tremor, rigidity, slowness of movement, and difficulty with walking. Cognitive and behavioral problems may also occur with depression, anxiety, and apathy occurring in many people with PD. Parkinson's disease dementia becomes common in the advanced stages of the disease. Those with Parkinson's can also have problems with their sleep and sensory systems. The motor symptoms of the disease result from the death of cells in the substantia nigra, a region of the midbrain, leading to a dopamine deficit. The cause of this cell death is poorly understood, but involves the build-up of misfolded proteins into Lewy bodies in the neurons. Collectively, the main motor symptoms are also known as ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Neurodegeneration
A neurodegenerative disease is caused by the progressive loss of structure or function of neurons, in the process known as neurodegeneration. Such neuronal damage may ultimately involve cell death. Neurodegenerative diseases include amyotrophic lateral sclerosis, multiple sclerosis, Parkinson's disease, Alzheimer's disease, Huntington's disease, multiple system atrophy, and prion diseases. Neurodegeneration can be found in the brain at many different levels of neuronal circuitry, ranging from molecular to systemic. Because there is no known way to reverse the progressive degeneration of neurons, these diseases are considered to be incurable; however research has shown that the two major contributing factors to neurodegeneration are oxidative stress and inflammation. Biomedical research has revealed many similarities between these diseases at the subcellular level, including atypical protein assemblies (like proteinopathy) and induced cell death. These similarities suggest that ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Clinical Decision Support System
A clinical decision support system (CDSS) is a health information technology, provides clinicians, staff, patients, or other individuals with knowledge and person-specific information, to help health and health care. CDSS encompasses a variety of tools to enhance decision-making in the clinical workflow. These tools include computerized alerts and reminders to care providers and patients, clinical guidelines, condition-specific order sets;´, focused patient data reports and summaries, documentation templates, diagnostic support, and contextually relevant reference information, among other tools. Robert Hayward of the Centre has proposed a working definition for Health Evidence: "Clinical decision support systems link health observations with health knowledge to influence health choices by clinicians for improved health care". CDSSs constitute a major topic in artificial intelligence in medicine. Characteristics A clinical decision support system is an active knowledge system that ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hillsborough County, Florida
Hillsborough County is located in the west central portion of the U.S. state of Florida. In the 2020 census, the population was 1,459,762, making it the fourth-most populous county in Florida and the most populous county outside the Miami metropolitan area. A 2021 estimate has the population of Hillsborough County at 1,512,070 people with a yearly growth rate of 1.34%, which itself is greater than the populations of 12 states according to their 2019 population estimates. Its county seat and largest city is Tampa, Florida, Tampa. Hillsborough County is part of the Tampa–St. Petersburg, Florida, St. Petersburg–Clearwater, Florida, Clearwater Tampa Bay Area, Metropolitan Statistical Area. History Hillsborough County was created on January 25, 1834, from Alachua County, Florida, Alachua and Monroe County, Florida, Monroe Counties, during the Florida Territory, U.S. territorial period (1822–1845). The new county was named for Wills Hill, 1st Marquess of Downshire, Wills Hill ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cash Flow
A cash flow is a real or virtual movement of money: *a cash flow in its narrow sense is a payment (in a currency), especially from one central bank account to another; the term 'cash flow' is mostly used to describe payments that are expected to happen in the future, are thus uncertain and therefore need to be forecast with cash flows; *a cash flow is determined by its time ''t'', nominal amount ''N'', currency ''CCY'' and account ''A''; symbolically ''CF'' = ''CF''(''t,N,CCY,A''). * it is however popular to use ''cash flow'' in a less specified sense describing (symbolic) payments into or out of a business, project, or financial product. Cash flows are narrowly interconnected with the concepts of value, ''interest rate'' and liquidity. A cash flow that shall happen on a future day ''t''N can be transformed into a cash flow of the same value in ''t''0. Cash flow analysis Cash flows are often transformed into measures that give information e.g. on a company's value and situat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Autoregressive Integrated Moving Average
In statistics and econometrics, and in particular in time series analysis, an autoregressive integrated moving average (ARIMA) model is a generalization of an autoregressive moving average (ARMA) model. Both of these models are fitted to time series data either to better understand the data or to predict future points in the series (forecasting). ARIMA models are applied in some cases where data show evidence of non-stationarity in the sense of mean (but not variance/autocovariance), where an initial differencing step (corresponding to the "integrated" part of the model) can be applied one or more times to eliminate the non-stationarity of the mean function (i.e., the trend). When the seasonality shows in a time series, the seasonal-differencing could be applied to eliminate the seasonal component. Since the ARMA model, according to the Wold's decomposition theorem, is theoretically sufficient to describe a regular (a.k.a. purely nondeterministic) wide-sense stationary time seri ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Unstructured Data
Unstructured data (or unstructured information) is information that either does not have a pre-defined data model or is not organized in a pre-defined manner. Unstructured information is typically text-heavy, but may contain data such as dates, numbers, and facts as well. This results in irregularities and ambiguities that make it difficult to understand using traditional programs as compared to data stored in fielded form in databases or annotated ( semantically tagged) in documents. In 1998, Merrill Lynch said "unstructured data comprises the vast majority of data found in an organization, some estimates run as high as 80%." It's unclear what the source of this number is, but nonetheless it is accepted by some. Other sources have reported similar or higher percentages of unstructured data. , IDC and Dell EMC project that data will grow to 40 zettabytes by 2020, resulting in a 50-fold growth from the beginning of 2010. More recently, IDC and Seagate predict that the global datas ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Text Analytics
Text mining, also referred to as ''text data mining'', similar to 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. (2005) we can distinguish between three different perspectives of text mining: information extraction, data mining, and a KDD (Knowledge Discovery in Databases) process. Text mining usually involves the process of structuring the input text (usually parsing, along with the addition of some derived linguistic features and the removal of others, and subsequent insertion into a database), deriving patterns within the structured data, and finally evaluation and inte ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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