Predicting the Survival Rate of Titanic Disaster Using Machine Learning Approaches

Jyothi Shetty; S. Pallavi

doi:10.1109/I2CT42659.2018.9058280

Predicting the Survival Rate of Titanic Disaster Using Machine Learning Approaches

Jyothi Shetty
, S. Pallavi
, Ramyashree

School of Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

The Titanic incident has led the scientist and investigators to comprehend what can have prompted the survival of a few travelers and death of the rest. Many machine learning algorithms contributed in predicting the survival rate of passengers. In addition to the this, a dataset of 891 rows which includes the attributes namely Age, PassengerID, Sex, Name, Embarked, Fare etc. has been used. In this paper, survival of passengers is figured out using various machine learning techniques namely decision tree, logistic regression and linear SVM. The main focus of this work is to differentiate between the three different machine learning algorithms to analyze the survival rate of traveller based on the accuracy.

Original language	English
Title of host publication	2018 4th International Conference for Convergence in Technology, I2CT 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538652329
DOIs	https://doi.org/10.1109/I2CT42659.2018.9058280
Publication status	Published - 10-2018
Event	4th International Conference for Convergence in Technology, I2CT 2018 - Mangalore, India Duration: 27-10-2018 → 28-10-2018

Publication series

Name	2018 4th International Conference for Convergence in Technology, I2CT 2018

Conference

Conference	4th International Conference for Convergence in Technology, I2CT 2018
Country/Territory	India
City	Mangalore
Period	27-10-18 → 28-10-18

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Computer Networks and Communications
Computer Science Applications
Energy Engineering and Power Technology
Mechanical Engineering
Education

Access to Document

10.1109/I2CT42659.2018.9058280

Cite this

Shetty, J., Pallavi, S., & Ramyashree (2018). Predicting the Survival Rate of Titanic Disaster Using Machine Learning Approaches. In 2018 4th International Conference for Convergence in Technology, I2CT 2018 Article 9058280 (2018 4th International Conference for Convergence in Technology, I2CT 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/I2CT42659.2018.9058280

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title = "Predicting the Survival Rate of Titanic Disaster Using Machine Learning Approaches",

abstract = "The Titanic incident has led the scientist and investigators to comprehend what can have prompted the survival of a few travelers and death of the rest. Many machine learning algorithms contributed in predicting the survival rate of passengers. In addition to the this, a dataset of 891 rows which includes the attributes namely Age, PassengerID, Sex, Name, Embarked, Fare etc. has been used. In this paper, survival of passengers is figured out using various machine learning techniques namely decision tree, logistic regression and linear SVM. The main focus of this work is to differentiate between the three different machine learning algorithms to analyze the survival rate of traveller based on the accuracy.",

author = "Jyothi Shetty and S. Pallavi and Ramyashree",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 4th International Conference for Convergence in Technology, I2CT 2018 ; Conference date: 27-10-2018 Through 28-10-2018",

year = "2018",

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doi = "10.1109/I2CT42659.2018.9058280",

language = "English",

series = "2018 4th International Conference for Convergence in Technology, I2CT 2018",

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Shetty, J, Pallavi, S & Ramyashree 2018, Predicting the Survival Rate of Titanic Disaster Using Machine Learning Approaches. in 2018 4th International Conference for Convergence in Technology, I2CT 2018., 9058280, 2018 4th International Conference for Convergence in Technology, I2CT 2018, Institute of Electrical and Electronics Engineers Inc., 4th International Conference for Convergence in Technology, I2CT 2018, Mangalore, India, 27-10-18. https://doi.org/10.1109/I2CT42659.2018.9058280

Predicting the Survival Rate of Titanic Disaster Using Machine Learning Approaches. / Shetty, Jyothi; Pallavi, S.; Ramyashree.
2018 4th International Conference for Convergence in Technology, I2CT 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 9058280 (2018 4th International Conference for Convergence in Technology, I2CT 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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PY - 2018/10

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N2 - The Titanic incident has led the scientist and investigators to comprehend what can have prompted the survival of a few travelers and death of the rest. Many machine learning algorithms contributed in predicting the survival rate of passengers. In addition to the this, a dataset of 891 rows which includes the attributes namely Age, PassengerID, Sex, Name, Embarked, Fare etc. has been used. In this paper, survival of passengers is figured out using various machine learning techniques namely decision tree, logistic regression and linear SVM. The main focus of this work is to differentiate between the three different machine learning algorithms to analyze the survival rate of traveller based on the accuracy.

AB - The Titanic incident has led the scientist and investigators to comprehend what can have prompted the survival of a few travelers and death of the rest. Many machine learning algorithms contributed in predicting the survival rate of passengers. In addition to the this, a dataset of 891 rows which includes the attributes namely Age, PassengerID, Sex, Name, Embarked, Fare etc. has been used. In this paper, survival of passengers is figured out using various machine learning techniques namely decision tree, logistic regression and linear SVM. The main focus of this work is to differentiate between the three different machine learning algorithms to analyze the survival rate of traveller based on the accuracy.

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M3 - Conference contribution

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T3 - 2018 4th International Conference for Convergence in Technology, I2CT 2018

BT - 2018 4th International Conference for Convergence in Technology, I2CT 2018

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Y2 - 27 October 2018 through 28 October 2018

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Shetty J, Pallavi S, Ramyashree. Predicting the Survival Rate of Titanic Disaster Using Machine Learning Approaches. In 2018 4th International Conference for Convergence in Technology, I2CT 2018. Institute of Electrical and Electronics Engineers Inc. 2018. 9058280. (2018 4th International Conference for Convergence in Technology, I2CT 2018). doi: 10.1109/I2CT42659.2018.9058280

Predicting the Survival Rate of Titanic Disaster Using Machine Learning Approaches

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