Titanic Survivor Prediction

Table of contents

• Introduction
• Data description
• Methods used
• Technologies used

Introduction

Project made in Jupyter Notebook with Kaggle Titanic dataset, which aims at detailed data analysis and prediction of which passengers survived the sinking of the Titanic.

Data description

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.

Methods used

• Cleaning Data
• Statistical Inference
• Exploratory Data Analysis (EDA)
• Data Visualization
• Supervised Machine Learning Algorithms: Logistic Regression, Random Forest, Naive Bayes, K-nearest Neighbors, SVC

Technologies used

• Python 3.8.8
• Pandas 1.2.4
• Matplotlib 3.3.4
• Seaborn 0.11.1
• Sklearn 0.24.1