• ISSN: 2349-6002
  • UGC Approved Journal No 47859
Author Login IJIRT Partner Network (IPN) Login

Learning From Disasters

  • Unique Paper ID: 160213
  • Volume: 10
  • Issue: 1
  • PageNo: 146-149
  • Abstract:
  • By using traditional machine learning algorithms, this study seeks to understand the relationship between the survival and mortality rates of passengers on the Titanic RMS. The passenger class, age, sex, passenger ID, and the number of siblings were all included in the dataset that was utilised for analysis, which was downloaded from the Kaggle website. Decision trees, random forests, xg-boost, the gradient boosting method, K-Nearest Neighbours, and logistic regression are just a few of the algorithms that are compared in terms of prediction accuracy in this study. Utilising the distinctive insights and extremely accurate numbers produced by each algorithm, the examination concentrates on the accuracy and precision of each approach. With the help of this study, we hope to advance our understanding of disaster analysis and offer new perspectives on how to make maritime accidents safer in the future
Download article email to a friend

Cite This Article

  • ISSN: 2349-6002
  • Volume: 10
  • Issue: 1
  • PageNo: 146-149

Learning From Disasters

Related Articles

Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

Join Our IPN

IJIRT Partner Network

Submit your research paper and those of your network (friends, colleagues, or peers) through your IPN account, and receive 800 INR for each paper that gets published.

Join Now

Latest Publication

Archive

View More

Recent Conferences

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024 Last Date: 15th March 2024

Submit inquiry