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Tracy De Poalo

dblp:151/3324 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2014
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-authorDatabases, data management, data science and information retrieval · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Data mining · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Data mining › predictive modeling › regression
logistic regression		 0.212014
Predictive modeling in practice: a case study from sprint · KDD 2014
Data mining
predictive modeling		 0.212014
Predictive modeling in practice: a case study from sprint · KDD 2014
Data mining › predictive modeling › classification › ensemble learning
random forest		 0.112014
Predictive modeling in practice: a case study from sprint · KDD 2014

Methods — techniques the papers use, named apart from their topics

random forest · 0.2logistic regression · 0.2
YearPublicationVenuePosition
2014 Predictive modeling in practice: a case study from sprint
abstract
It's not often we get to peer into the details of how big corporates use predictive modeling in practice. In this talk, Sprint's Head of Predictive Modeling, Tracey De Poalo, will talk about the process she developed using SAS and logistic regression to build a wide range of models. Jeremy Howard will discuss his experience as a consultant at Sprint comparing R and random forests to the existing process, and will show the pros and cons of each approach.
Tracy De Poalo, Jeremy Howard
 KDD1