Titanic-Machine-Learning-from-Disaster

Titanic: Machine Learning from Disaster

This model is based on Logistic Regression.

1. The data used to determine my outcome is avalable on the data folder or can be found from the competition page.
2. Data folder contains:
   • gender_submission.csv - A sample formate for output submission
   • test.csv - Test dataset
   • train.csv - Train dataset
3. titanic_survival.ipynb contains the code for data preprocessing and modeling.
4. submission.csv is the outcome of the data modeling.

Data Discription

Variable	Definition	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.