https://www.kaggle.com/c/titanic Kaggle
- Task is predict who is serviving and who has better servival rate
we have 10692 train data
trian data set contain:
- PassengerId
- Survived
- Pclass
- Name
- Sex
- Age
- SibSp
- Parch
- Ticket
- Fare
- Cabin
- Embarked
SO, Firstly i check how mane servivers are thier and map the servival relationship to get idea about the data
so i get the image with age and class.
After that i create servived relation ship with gender
in that image i found a clear relationship servived with gender. lot of females are sevived according to data.
after that i create hypothis that all female are servived and check with data and i got 78% accuracy.[predict_gender.py]]
i use logistioc regression to get more accurace and i got 79%.
from decision tree model it got 97% accuracy but after normalize it finaly i got 81% accurace.
Used tech:
- python
- MatplotLib
- sklearn
- numpy
- pandas
Thank You!
Hirusha R.