Titanic Traveller Survivability Prediction

Related tags

Machine Learningkaggle-titanicpython-3scikitlearn-machine-learningclassification-algorithmkaggle-dataset
Overview

Titanic Traveller Survivability Prediction

The aim of the mini project is predict whether or not a passenger survived based on attributes such as their age, sex, passenger class, where they embarked and more.

The data is sourced from the Kaggle Titanic dataset. The data is split into two groups:

  1. Training Set
  2. Testing Set

Data Dictionary

Variable Description Key
survival Survival 0 = No, 1 = Yes
pclass Ticket class 1 = 1st, 2 = 2nd, 3 = 3rd
sex sex
Age Age in years
sibsp # of siblings / spouses aboard the Titanic
parch # of parents / children aboard the Titanic
ticket Ticket number
fare Passenger fare
cabin Cabin number
embarked Port of Embarkation C = Cherbourg, Q = Queenstown, S = Southampton

Variable Notes

pclass: A proxy for socio-economic status (SES) 1st = Upper 2nd = Middle 3rd = Lower

age: Age is fractional if less than 1. If the age is estimated, is it in the form of xx.5

sibsp: The dataset defines family relations in this way... Sibling = brother, sister, stepbrother, stepsister Spouse = husband, wife (mistresses and fiancés were ignored)

parch: The dataset defines family relations in this way... Parent = mother, father Child = daughter, son, stepdaughter, stepson Some children travelled only with a nanny, therefore parch=0 for them.

Requirements

  • Pandas
  • Scikit-Learn
  • Matplotlib
  • Numpy
Owner
John Phillip
Software developer, main tools are C++, Python, and SQL. Interested in Robotics, A.I, and Machine Learning
John Phillip
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