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.

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 day...

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Main Authors:	Andersson, Martin, Mazouch, Marcus
Format:	Others
Language:	English
Published:	Umeå universitet, Institutionen för matematik och matematisk statistik 2019
Subjects:	statistics classification machine learning logistic regression support vector machine rbf significance prediction propensity to buy flight tickets ai artificiell intelligens walds test sas scandinavian airlines statistik klassificering maskininlärning signifikans prediktion benägenhet att köpa biljett flyg artificial intelligence Probability Theory and Statistics Sannolikhetsteori och statistik
Online Access:	http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-160855

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spelling	ndltd-UPSALLA1-oai-DiVA.org-umu-1608552019-08-13T04:27:33ZBinary 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.engSvensk titel: Binär klassificering applicerat på att prediktera benägenhet att köpa flygbiljetter.Andersson, MartinMazouch, MarcusUmeå universitet, Institutionen för matematik och matematisk statistikUmeå universitet, Institutionen för matematik och matematisk statistik2019statisticsclassificationmachine learninglogistic regressionsupport vector machinerbfsignificancepredictionpropensity to buyflightticketsaiartificiell intelligenswalds testsasscandinavian airlinesstatistikklassificeringmaskininlärninglogistic regressionsupport vector machinerbfsignifikanswalds testprediktionbenägenhet att köpaflightbiljettflygaiartificial intelligencesasscandinavian airlinesProbability Theory and StatisticsSannolikhetsteori och statistikA 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 and search history is showed to be insignificant. En kunds benägenhet att göra ett visst köp är ett allmänt undersökt område som applicerats i flera olika branscher. I den här studien visas det att statistiska binära klassificeringsmodeller kan användas för att prediktera Scandinavian Airlines kunders benägenhet att köpa en resa de kommande sju dagarna. En jämförelse är presenterad mellan logistisk regression och stödvektormaskin och logistisk regression med reducerat antal parametrar väljs som den slutgiltiga modellen tack vare sin enkelhet och träffsäkerhet. De förklarande variablerna är uteslutande bokningshistorik medan kundens demografi och sökdata visas vara insignifikant. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-160855application/pdfinfo:eu-repo/semantics/openAccess
collection	NDLTD
language	English
format	Others
sources	NDLTD
topic	statistics classification machine learning logistic regression support vector machine rbf significance prediction propensity to buy flight tickets ai artificiell intelligens walds test sas scandinavian airlines statistik klassificering maskininlärning logistic regression support vector machine rbf signifikans walds test prediktion benägenhet att köpa flight biljett flyg ai artificial intelligence sas scandinavian airlines Probability Theory and Statistics Sannolikhetsteori och statistik
spellingShingle	statistics classification machine learning logistic regression support vector machine rbf significance prediction propensity to buy flight tickets ai artificiell intelligens walds test sas scandinavian airlines statistik klassificering maskininlärning logistic regression support vector machine rbf signifikans walds test prediktion benägenhet att köpa flight biljett flyg ai artificial intelligence sas scandinavian airlines Probability Theory and Statistics Sannolikhetsteori och statistik Andersson, Martin Mazouch, Marcus 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.
description	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 and search history is showed to be insignificant. === En kunds benägenhet att göra ett visst köp är ett allmänt undersökt område som applicerats i flera olika branscher. I den här studien visas det att statistiska binära klassificeringsmodeller kan användas för att prediktera Scandinavian Airlines kunders benägenhet att köpa en resa de kommande sju dagarna. En jämförelse är presenterad mellan logistisk regression och stödvektormaskin och logistisk regression med reducerat antal parametrar väljs som den slutgiltiga modellen tack vare sin enkelhet och träffsäkerhet. De förklarande variablerna är uteslutande bokningshistorik medan kundens demografi och sökdata visas vara insignifikant.
author	Andersson, Martin Mazouch, Marcus
author_facet	Andersson, Martin Mazouch, Marcus
author_sort	Andersson, Martin
title	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.
title_short	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.
title_full	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.
title_fullStr	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.
title_full_unstemmed	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.
title_sort	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.
publisher	Umeå universitet, Institutionen för matematik och matematisk statistik
publishDate	2019
url	http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-160855
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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.

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