O'Reilly on Data

JANUARY 22, 2019

They trade the markets using quantitative models based on non-financial theories such as information theory, data science, and machine learning. 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. Baggett, W.C.

Modeling 134

Modeling Finance Uncertainty Data mining 134

BizAcuity

APRIL 28, 2019

is delinquent as of June 30th, 2017. With Big Data, it is possible to acquire and segregate data with laser sharp focus with respect to one singular debtor. By clubbing various techniques like data mining, machine learning, artificial intelligence and statistical modelling, it makes predictions about events in the future.

Predictive Analytics 98

Predictive Analytics Analytics Big Data Data mining 98

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

The Unofficial Google Data Science Blog

JULY 22, 2020

by ALEXANDER WAKIM Ramp-up and multi-armed bandits (MAB) are common strategies in online controlled experiments (OCE). These strategies involve changing assignment weights during an experiment. The first is a strategy called ramp-up and is advised by many experts in the field [1].

Experimentation 95

Experimentation Statistics Testing Strategy 95

Domino Data Lab

MAY 20, 2021

propose a different strategy where the minority class is over-sampled by generating synthetic examples. This carries the risk of this modification performing worse than simpler approaches like majority under-sampling. The class imbalance problem: Significance and strategies. In their 2002 paper Chawla et al. Chawla et al.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

The Unofficial Google Data Science Blog

APRIL 23, 2024

It is also a sound strategy when experimenting with several parameters at the same time. To find optimal values of two parameters experimentally, the obvious strategy would be to experiment with and update them in separate, sequential stages. (And sometimes even if it is not[1].) Why experiment with several parameters concurrently?

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

datapine

NOVEMBER 27, 2019

In 2020, BI tools and strategies will become increasingly customized. It is not only important to gather as much information possible, but the quality and the context in which data is being used and interpreted serves as the main focus for the future of business intelligence. Source: Business Application Research Center *.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361