Predictive analytics: Difference between revisions

Revision as of 23:06, 27 March 2025

Revision as of 00:45, 6 June 2025

Line 2:

{{More citations needed|date=June 2011}}

'''Predictive analytics''', or '''predictive AI''', 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 [[prediction]]s about future or otherwise unknown events.<ref name=":52">{{Cite web |title=To predict or not to Predict |url=https://mccoy-partners.com/updates/to-predict-or-not-to-predict |access-date=2022-05-05 |website=mccoy-partners.com}}</ref>

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.<ref>{{Cite book |last=Coker |first=Frank |title=Pulse: Understanding the Vital Signs of Your Business (1st ed.) |___location=Bellevue, WA |publisher=Ambient Light Publishing |year=2014 |isbn=978-0-9893086-0-1 |pages=30, 39, 42, more}}</ref>