Results 161 to 170 of about 1,692 (204)

Integrating generative AI and machine learning classifiers for solving heterogenous MCGDM: a case of employee churn prediction. [PDF]

Sci Rep
Abu-Faty HG, Kafafy A, Hadhoud MM, Abdel-Raouf O.   +3 more
europepmc   +1 more source

Synthesizing Explainability Across Multiple ML Models for Structured Data. [PDF]

Algorithms
Veledar E, Zhou L, Veledar O, Gardener H, Gutierrez CM, Romano JG, Rundek T.   +6 more
europepmc   +1 more source

Determining human resource management key indicators and their impact on organizational performance using deep reinforcement learning. [PDF]

Sci Rep
Sun Z.
europepmc   +1 more source

The adaptive engagement framework: enhancing banking customer experience through AI-powered invisible marketing. [PDF]

Sci Rep
Shahbazi A, Behtaji S, Tajiki AH, Şirzad N, Darvishan S, Najafzadeh H.   +5 more
europepmc   +1 more source

An autonomous mixed data oversampling method for AIOT-based churn recognition and personalized recommendations using behavioral segmentation. [PDF]

PeerJ Comput Sci
Fatima G, Khan S, Aadil F, Kim DH, Atteia G, Alabdulhafith M.   +5 more
europepmc   +1 more source

Managing inventories for perishable e-groceries: The value of probabilistic information. [PDF]

PLoS One
Winkelmann D, Ulrich M, Römer M, Langrock R, Jahnke H.   +4 more
europepmc   +1 more source

Enterprise service user intent prediction based on fast K-means++ fusion algorithm. [PDF]

PLoS One
Han Y, Zhai J, Li P.
europepmc   +1 more source

Social network analysis for customer churn prediction

Applied Soft Computing Journal, 2014
This study examines the use of social network information for customer churn prediction. An alternative modeling approach using relational learning algorithms is developed to incorporate social network effects within a customer churn prediction setting, in order to handle large scale networks, a time dependent class label, and a skewed class ...
Wouter Verbeke, David Martens, Bart Baesens   +2 more
exaly   +5 more sources

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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.
Tahar Kechadi
exaly   +2 more sources

ADTreesLogit model for customer churn prediction

Annals of Operations Research, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhou, Y, Li, L, Qi, J, Zhang, L, Liu, Y, Liang, L, Li, H, Shen, Y   +7 more
openaire   +5 more sources