Results 181 to 190 of about 1,523,124 (234)

Survival analysis of electric vehicle charging behavior and the temporal evolution of feature effects. [PDF]

Sci Rep
Meža M, Strle G, Meža M.
europepmc   +1 more source

A comprehensive dataset of customer behavior in Latin American Fintech: 12-month transactional and demographic data for churn analysis. [PDF]

Data Brief
Muñoz-Guerrero LE, Ceballos YF, Trejos-Rojas LD.   +2 more
europepmc   +1 more source

A Data-Driven Framework for Class Overlap Reduction to Improve Soft Sensor Performance. [PDF]

Sensors (Basel)
Nugraha FW, Shwe T, Mendonça I, Aritsugi M.   +3 more
europepmc   +1 more source

Multistructural and Multiscale Instability Characterization of Gas-Liquid Two-Phase Flow with MRA-CMESSE. [PDF]

Entropy (Basel)
Sun QM, Yu QC, Ba D.
europepmc   +1 more source

A unified privacy-preserving data mining framework with multi-noise injection and hybrid deep learning for robust privacy-utility trade-offs. [PDF]

Sci Rep
Arun R, Premalatha K, Kannimuthu S.
europepmc   +1 more source

Evidence of unreliable data and poor data provenance in clinical prediction model research and clinical practice. [PDF]

BMC Med
Gibson AD, White NM, Collins GS, Barnett AG.   +3 more
europepmc   +1 more source

Multiscale Characterization of Flow Instability for Gas-Liquid Two-Phase Flow. [PDF]

Entropy (Basel)
Sun QM, Yu QC, Ba D, Du Y.
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Customer churn prediction in telecommunications

Expert Systems With Applications, 2012
This paper presents a new set of features for land-line customer churn prediction, including 2 six-month Henley segmentation, precise 4-month call details, line information, bill and payment information, account information, demographic profiles, service orders, complain information, etc.
Mohand Tahar Kechadi
exaly   +2 more sources

Customer Churn Prediction in B2B Contexts

, 2019
While business-to-customer (B2C) companies, in the telecom sector for instance, have been making use of customer churn prediction for many years, churn prediction in the business-to-business (B2B) domain receives much less attention in existing literature.
Iris Figalist, Christoph Elsner, Jan Bosch, Helena Holmström Olsson   +3 more
openaire   +3 more sources

CHURN PREDICTION WITH MACHINE LEARNING

, 2022
Churn Prediction is used to predict if a particular customer has a high possibility of churn if there is still time to resolve this issue. • It aids businesses in gaining huge revenue potential.
ORR ELIZABETH MARJORY, JOHNSON GARY TODD, BANERJEE NEEL   +2 more
core   +4 more sources