O'Reilly on Data

JANUARY 22, 2019

Whether financial models are based on academic theories or empirical data mining strategies, they are all subject to the trinity of modeling errors explained below. Time-variant distributions for asset values and risks are the rule, not the exception. Suppose after the fifth meeting in our example, the U.S.

Modeling 133

Modeling Finance Uncertainty Data mining 133

datapine

NOVEMBER 27, 2019

This is one of the major trends chosen by Gartner in their 2020 Strategic Technology Trends report , combining AI with autonomous things and hyperautomation, and concentrating on the level of security in which AI risks of developing vulnerable points of attacks. It’s an extension of data mining which refers only to past data.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Domino Data Lab

MAY 20, 2021

This carries the risk of this modification performing worse than simpler approaches like majority under-sampling. note that this variant “performs worse than plain under-sampling based on AUC” when tested on the Adult dataset (Dua & Graff, 2017). Data mining for direct marketing: Problems and solutions. Chawla et al.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

bridgei2i

JULY 28, 2020

She’s the founder and CEO of StatWeather, a company, which was recognized as number one in climate technology globally in the year, 2017, by the Energy Risk Awards. So, then we need systems, analysts, database administrators, people who can set in place, these types of backup systems for risk management. Not just that.

Enterprise 98

Enterprise Digital Transformation Insurance B2B 98