New to Machine Learning? Then you must have been struggling with this problem. No worries. This project has the codes which has varied amount of accuracies and applies different machine learning algorithms to train and classify the data and help in awesome predictions.
Problem Statement:
The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 1502 out of 2224 passengers and crew. This sensational tragedy shocked the international community and led to better safety regulations for ships.
One of the reasons that the shipwreck led to such loss of life was that there were not enough lifeboats for the passengers and crew. Although there was some element of luck involved in surviving the sinking, some groups of people were more likely to survive than others, such as women, children, and the upper-class.
In this challenge, we ask you to complete the analysis of what sorts of people were likely to survive. In particular, we ask you to apply the tools of machine learning to predict which passengers survived the tragedy.
The link to the problem: Titanic
The codes run on Python3.
Usage:
1> Run the command:
sudo apt-get install python-pip
2>Install sci-kit learn. Run the command:
pip install -U scikit-learn
3>Install numpy. Run the command:
sudo pip install numpy scipy
4>Go to you local repository where this project has been saved through cd </path>. Now run the command:
python <filename>.py
Here if you choose filename to be decisionTreeImplementation two csv files result1.csv and result3.csv will be generated which you can submit to Kaggle and see your
accuracy. result1.csv will give upto 63% accuracy while result3.csv will give upto 73% accuracy.
And if you choose the filename to be randomforestImplementation.py, it will generate a csv file result4.csv which will give upto 72% of accuracy.