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Customer churn prediction model based on hybrid neural networks. [PDF]
Sci RepLiu X, Xia G, Zhang X, Ma W, Yu C.
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Revolutionizing market surveillance: customer relationship management with machine learning. [PDF]
PeerJ Comput SciShi X, Zhang Y, Yu M, Zhang L.
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Confronting the inevitable: Harnessing technology to contain systemic scientific fraud. [PDF]
Proc Natl Acad Sci U S ASinger P.
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Adaptive rateless coded blockchain for dynamic IoV scenarios. [PDF]
Sci RepZhang S +4 more
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Entrapment in games: Reframing persistence in the I-PACE framework. [PDF]
J Behav AddictStrojny P, Kłosiński M.
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Cell Complexity Impact on Railway 5G Performance: Measurements Along Tallinn-Tartu Corridor. [PDF]
Sensors (Basel)Pilvik R +3 more
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US Coverage Changes During Medicaid Unwinding in 2023.
JAMA Health ForumMcIntyre A +4 more
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Expert Systems With Applications, 2011
Customer churn is a notorious problem for most industries, as loss of a customer affects revenues and brand image and acquiring new customers is difficult. Reliable predictive models for customer churn could be useful in devising customer retention plans.
Girish Keshav Palshikar
exaly +2 more sources
Customer churn is a notorious problem for most industries, as loss of a customer affects revenues and brand image and acquiring new customers is difficult. Reliable predictive models for customer churn could be useful in devising customer retention plans.
Girish Keshav Palshikar
exaly +2 more sources