Predicting Malawi Travel Costs - A Machine Learning Approach to Travel Planning

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https://hdl.handle.net/2142/133116

Title: Predicting Malawi Travel Costs - A Machine Learning Approach to Travel Planning
Author(s): Kamwela, Josephine
Contributor(s): Kang, Peng
Issue Date: 2026
Keyword(s): machine learning model; travel
Date of Ingest: 2026-04-16T14:04:05-05:00
Abstract: Presented at STARS 2026. My project, Predicting Malawi Travel Costs, focused on building a data‑driven machine learning model to estimate the total cost of travel to Malawi based on factors such as accommodation, transportation, food, and activity expenses. I collected and cleaned real travel‑related data, performed exploratory data analysis, engineered relevant features, and trained multiple predictive models to identify the most accurate approach. I also created a final presentation and written report summarizing the methodology, model performance, and practical applications of the system for travelers, tourism planners, and economic development stakeholders.
Type of Resource: text
Genre of Resource: conference proceeding

Student work presented at STARS