This repository contains the code that achieves 76% score in the Kaggle Titanic Competition The code was developed to serve as an initial exploration of Scikit-Learn.
To achieve the result, the following were the pre-processing techniques applied:
- [Age], [Fare]: Missing Values were handled with Mean
- [Embarked]: Missing values were handled with Most Frequent Strategy
- [Embarked]: One Hot Encoder applied
- [Sex]: Ordinal Encoder applied
- [Age], [SibSp], [Fare], [Pclass]: Numerical Features that were normalized with MinMaxScaler
The model built in this implementation is a simple Logistic Regression Model