This is a challenge on Kaggle to predict whether a person survives or not on the Titanic depending on the features given using Machine Learning
- I used different types of classifiers like
DecisionTrees
,KNearest-Neighbours
andGradient Boosting
. - I used
cross-validation
to increase the performance of the model i.e. to select the best algorithm. - I also pre-processed the data to fill any null values present, encode non-numerical data and remove unwated features.
- I got 79.9% Accuracy using the
Gradient Boosting
algorithm.
- scikit-learn
- Pandas
- Numpy
- matplotlib