Airline flight delay prediction using Naïve Bayes algorithm / Ahmad Adib Baihaqi Shukri

The aviation industry plays a critical role in global transportation, facilitating economic growth and revolutionizing travel. However, flight delays have become a growing concern, impacting both airlines and passengers. This study aims to study the Naïve Bayes algorithm for flight delay prediction....

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Main Author:	Shukri, Ahmad Adib Baihaqi
Format:	Thesis
Language:	English
Published:	2024
Subjects:	Evolutionary programming (Computer science) Genetic algorithms
Online Access:	https://ir.uitm.edu.my/id/eprint/96295/1/96295.pdf
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id	my-uitm-ir.96295
record_format	uketd_dc
spelling	my-uitm-ir.962952024-06-04T07:20:25Z Airline flight delay prediction using Naïve Bayes algorithm / Ahmad Adib Baihaqi Shukri 2024 Shukri, Ahmad Adib Baihaqi Evolutionary programming (Computer science). Genetic algorithms The aviation industry plays a critical role in global transportation, facilitating economic growth and revolutionizing travel. However, flight delays have become a growing concern, impacting both airlines and passengers. This study aims to study the Naïve Bayes algorithm for flight delay prediction. The objective is to develop a reliable flight delay prediction model using the Naïve Bayes algorithm and evaluate its performance. The data set that records flight delay and cancellation data from U.S Department of Transportation’s (DOT) was used for the prediction. Three algorithms (Gaussian Naïve Bayes, K-Nearest Neighbors (KNN) and Support Vector Machine (SVM)) were trained and tested to complete the binary classification of flight delays. Parameter tuning also done on Gaussian Naïve Bayes by changing its parameter. The evaluation of algorithms was fulfilled by comparing the values of accuracy, specificity and ROC AUC score. These measures were weighted to adjust the imbalance of the selected data set. The comparative analysis showed that the Gaussian Naïve Bayes has the best performance with an accuracy of 93% and KNN has the worst performance with ROC AUC score 63%. The Naïve Bayes classifier generally have better performance over other base classifiers. 2024 Thesis https://ir.uitm.edu.my/id/eprint/96295/ https://ir.uitm.edu.my/id/eprint/96295/1/96295.pdf text en public degree Universiti Teknologi MARA, Terengganu College of Computing, Informatics and Mathematics Mohamed Yusoff, Syarifah Adilah
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Mohamed Yusoff, Syarifah Adilah
topic	Evolutionary programming (Computer science) Genetic algorithms
spellingShingle	Evolutionary programming (Computer science) Genetic algorithms Shukri, Ahmad Adib Baihaqi Airline flight delay prediction using Naïve Bayes algorithm / Ahmad Adib Baihaqi Shukri
description	The aviation industry plays a critical role in global transportation, facilitating economic growth and revolutionizing travel. However, flight delays have become a growing concern, impacting both airlines and passengers. This study aims to study the Naïve Bayes algorithm for flight delay prediction. The objective is to develop a reliable flight delay prediction model using the Naïve Bayes algorithm and evaluate its performance. The data set that records flight delay and cancellation data from U.S Department of Transportation’s (DOT) was used for the prediction. Three algorithms (Gaussian Naïve Bayes, K-Nearest Neighbors (KNN) and Support Vector Machine (SVM)) were trained and tested to complete the binary classification of flight delays. Parameter tuning also done on Gaussian Naïve Bayes by changing its parameter. The evaluation of algorithms was fulfilled by comparing the values of accuracy, specificity and ROC AUC score. These measures were weighted to adjust the imbalance of the selected data set. The comparative analysis showed that the Gaussian Naïve Bayes has the best performance with an accuracy of 93% and KNN has the worst performance with ROC AUC score 63%. The Naïve Bayes classifier generally have better performance over other base classifiers.
format	Thesis
qualification_level	Bachelor degree
author	Shukri, Ahmad Adib Baihaqi
author_facet	Shukri, Ahmad Adib Baihaqi
author_sort	Shukri, Ahmad Adib Baihaqi
title	Airline flight delay prediction using Naïve Bayes algorithm / Ahmad Adib Baihaqi Shukri
title_short	Airline flight delay prediction using Naïve Bayes algorithm / Ahmad Adib Baihaqi Shukri
title_full	Airline flight delay prediction using Naïve Bayes algorithm / Ahmad Adib Baihaqi Shukri
title_fullStr	Airline flight delay prediction using Naïve Bayes algorithm / Ahmad Adib Baihaqi Shukri
title_full_unstemmed	Airline flight delay prediction using Naïve Bayes algorithm / Ahmad Adib Baihaqi Shukri
title_sort	airline flight delay prediction using naïve bayes algorithm / ahmad adib baihaqi shukri
granting_institution	Universiti Teknologi MARA, Terengganu
granting_department	College of Computing, Informatics and Mathematics
publishDate	2024
url	https://ir.uitm.edu.my/id/eprint/96295/1/96295.pdf
_version_	1804889984010813440

Airline flight delay prediction using Naïve Bayes algorithm / Ahmad Adib Baihaqi Shukri

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