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Relevant bibliographies by topics / Classification of customers

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Dissertations / Theses

Academic literature on the topic 'Classification of customers'

Author: Grafiati

Published: 30 May 2022

Last updated: 31 May 2022

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Dissertations / Theses on the topic "Classification of customers"

1

CARVALHO, NORMA ALICE DA SILVA. "HYBRID INTELLIGENT SYSTEM FOR CLASSIFICATION OF NON-RESIDENTIAL ELECTRICITY CUSTOMERS PAYMENT PROFILES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2016. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=33393@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>PROGRAMA DE SUPORTE À PÓS-GRADUAÇÃO DE INSTS. DE ENSINO<br>O objetivo desta pesquisa é classificar o perfil de pagamento dos consumidores não-residenciais de energia elétrica, considerando conhecimento armazenado em base de dados de distribuidoras de energia elétrica. A motivação para desenvolvê-la surgiu da necessidade das distribuidoras por um modelo de suporte a formulação de estratégias capazes de reduzir o grau inadimplência. A metodologia proposta consiste em um sistema i

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2

Kirkin, S., and K. V. Melnyk. "Intelligent Data Processing in Creating Targeted Advertising." Thesis, National Technical University "Kharkiv Polytechnic Institute", 2017. http://repository.kpi.kharkov.ua/handle/KhPI-Press/44710.

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3

Andersson, Martin, and Marcus Mazouch. "Binary classification for predicting propensity to buy flight tickets. : A study on whether binary classification can be used to predict Scandinavian Airlines customers’ propensity to buy a flight ticket within the next seven days." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-160855.

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A customers propensity to buy a certain product is a widely researched field and is applied in multiple industries. In this thesis it is showed that using binary classification on data from Scandinavian Airlines can predict their customers propensity to book a flight within the next coming seven days. A comparison between logistic regression and support vector machine is presented and logistic regression with reduced number of variables is chosen as the final model, due to it’s simplicity and accuracy. The explanatory variables contains exclusively booking history, whilst customer demographics

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4

Mazouch, Marcus, and Martin Andersson. "Binary classification for predicting propensity to buy flight tickets : A study on whether binary classification can be used to predict Scandinavian Airlines customers' propensity to buy a flight ticket within the next seven days." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-162412.

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A customers propensity to buy a certain product is a widely researched field and is applied in multiple industries. In this thesis it is showed that using binary classification on data from Scandinavian Airlines can predict their customers propensity to book a flight within the next coming seven days. A comparison between logistic regression and support vector machine is presented and logistic regression with reduced number of variables is chosen as the final model, due to it's simplicity and accuracy. The explanatory variables contains exclusively booking history, whilst customer demographics

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5

Eriksson, Alexander, and Jacob Långström. "Comparison of Machine Learning Techniques when Estimating Probability of Impairment : Estimating Probability of Impairment through Identification of Defaulting Customers one year Ahead of Time." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-160114.

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Probability of Impairment, or Probability of Default, is the ratio of how many customers within a segment are expected to not fulfil their debt obligations and instead go into Default. This is a key metric within banking to estimate the level of credit risk, where the current standard is to estimate Probability of Impairment using Linear Regression. In this paper we show how this metric instead can be estimated through a classification approach with machine learning. By using models trained to find which specific customers will go into Default within the upcoming year, based on Neural Networks

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6

Axén, Maja, and Jennifer Karlberg. "Binary Classification for Predicting Customer Churn." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-171892.

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Predicting when a customer is about to turn to a competitor can be difficult, yet extremely valuable from a business perspective. The moment a customer stops being considered a customer is known as churn, a widely researched topic in several industries when dealing with subscription-services. However, in industries with non-subscription services and products, defining churn can be a daunting task and the existing literature does not fully cover this field. Therefore, this thesis can be seen as a contribution to current research, specially when not having a set definition for churn. A definitio

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7

Vallaud, Thierry. "Estimating potential customer value using customer data : using a classification technique to determine customer value /." Abstract and full text available, 2009. http://149.152.10.1/record=b3077978~S16.

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Thesis (M.S.) -- Central Connecticut State University, 2009.<br>Thesis advisor: Daniel Larose. "... in partial fulfillment of the requirements for the degree of Master of Science in Data Mining." Includes bibliographical references (leaves 37-39). Also available via the World Wide Web.

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8

Koch-Falkenberg, Carolyn. "Kundenloyalität in Dienstleistungsbeziehungen: untersucht am Beispiel der Deutschen Bahn AG." Universitätsverlag der Technischen Universität Chemnitz, 2018. https://monarch.qucosa.de/id/qucosa%3A35451.

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Warum sind Reisekunden der DB AG spezielle Kunden, deren Loyalität vergleichsweise wenig belastbar und besonders leicht zu verletzen ist? Was unterminiert ihre Leidenschaft für das Bahnfahren? Warum ist selbst für den Quasimonopolisten DB AG die Förderung einer uneingeschränkten Loyalität seiner Reisekunden relevant? Was charakterisiert die Bindung des Loyalitätstypus alter Art? Und was kennzeichnet die Entwicklung und spezifische Funktionsweise der Bindung des Loyalitätstypus neuer Art? Mit diesen Fragen greift die Autorin das Schnittstellenthema ‚Kundenloyalität in Dienstleistungsbeziehungen

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9

Colesky, Theo. "A Comparative Study on Customs Tariff Classification." Thesis, University of Pretoria, 2014. http://hdl.handle.net/2263/42838.

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The field of customs is commonly referred to as that of imports and exports. It is perceived as a maze of processes, procedures, and forms required to enable a customs administration to perform their wide range of responsibilities. One of the responsibilities of a customs administration is the collection of duties, which necessitates classification of the goods in question. This study sets out to determine the extent of customs control in relation to tariff classification in South Africa. The starting point is the establishment of the foundations of customs, both internationally and in Sou

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10

Pettersson, Anders. "High-Dimensional Classification Models with Applications to Email Targeting." Thesis, KTH, Matematisk statistik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-168203.

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Email communication is valuable for any modern company, since it offers an easy mean for spreading important information or advertising new products, features or offers and much more. To be able to identify which customers that would be interested in certain information would make it possible to significantly improve a company's email communication and as such avoiding that customers start ignoring messages and creating unnecessary badwill. This thesis focuses on trying to target customers by applying statistical learning methods to historical data provided by the music streaming company Spoti

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