2. z
Introduction
WOULD YOU SURVIVE THE TITANIC?
Our sample dataset: passengers of the Titanic. We will use an open data set
with data on the passengers aboard the infamous doomed sea voyage of 1912.
By examining factors such as class, sex, and age, we will experiment with
different machine learning algorithms and build a program that can predict
whether a given passenger would have survived this disaster.
3. z
Domain
Data Science
What is Data Science?
Data science is the field of study that combines domain
expertise, programming skills, and knowledge of mathematics
and statistics to extract meaningful insights from data. Data
science practitioners apply machine learning algorithms to
numbers, text, images, video, audio, and more to produce
artificial intelligence (AI) systems to perform tasks that ordinarily
require human intelligence. In turn, these systems generate
insights which analysts and business users can translate into
tangible business value.
4. z
General Aspects and technology
R programming
R studio
Packages
Clustering Algorithm
Visualization
Kaggle Dataset
Kaggle competition
5. z
Implementation
THE DATA AT FIRST GLANCE: WHO SURVIVED THE TITANIC AND WHY?
The column heading variables have the following meanings:
survival: Survival (0 = no; 1 = yes)
class: Passenger class (1 = first; 2 = second; 3 = third)
name: Name
sex: Sex
age: Age
sibsp: Number of siblings/spouses aboard
parch: Number of parents/children aboard
ticket: Ticket number
fare: Passenger fare
cabin: Cabin
embarked: Port of embarkation (C = Cherbourg; Q = Queenstown; S = Southampton)
boat: Lifeboat (if survived)
body: Body number (if did not survive and body was recovered)
6. z
CLASSIFICATION
The tree first splits by sex, and then by class, since it has learned during the
training phase that these are the two most important features for determining
survival. The dark blue boxes indicate passengers who are likely to survive,
and the dark orange boxes represent passengers who are almost certainly
doomed. Interestingly, after splitting by class, the main deciding factor
determining the survival of women is the ticket fare that they paid, while the
deciding factor for men is their age (with children being much more likely to
survive).