Back تحليلات تنبؤية Arabic Prädiktive Analytik German Análisis predictivo Spanish Prognoosiv analüüs Estonian تحلیل پیشگویانه Persian Analyse prédictive French Analitik prediktif ID Analisi predittiva Italian 予測分析 Japanese 예측 분석 Korean
 | This article needs additional citations for verification. (June 2011) |
Predictive analytics is a form of business analytics applying machine learning to generate a predictive model for certain business applications. As such, it encompasses a variety of statistical techniques from predictive modeling and machine learning that analyze current and historical facts to make predictions about future or otherwise unknown events.[1] It represents a major subset of machine learning applications; in some contexts, it is synonymous with machine learning.[2]
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.[3]
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 detection, manufacturing, healthcare, and government operations including law enforcement.
- ^ "To predict or not to Predict". mccoy-partners.com. Retrieved 2022-05-05.
- ^ Siegel, Eric (2013). Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die (1st ed.). Wiley. ISBN 978-1-1183-5685-2.
- ^ Coker, Frank (2014). Pulse: Understanding the Vital Signs of Your Business (1st ed.). Bellevue, WA: Ambient Light Publishing. pp. 30, 39, 42, more. ISBN 978-0-9893086-0-1.