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Jupyter Notebook 100.00%
titanic-jupyter-notebook titanic competition dataset kaggle analysis jupyter-notebook python pyhton3 kaggle-competition kaggle-titanic kaggle-titanic-survival survival survival-prediction survival-analysis titanic-kaggle titanic-survival-prediction data-analysis machine-learning machine-learning-algorithms

titanic-survivors's Introduction

About

This repository is related to the Kaggle competition: Titanic: Machine Learning from Disaster

In this competition, it is given a dataset (train.csv), with the survivors indications, and you must predict the output of a desired dataset (test.csv), if each person will survived or not.

Analysis

You can check my analysis in the Titanic Jupyter-notebook.

It's a little bit tricky to deal with some features (some of them has more than 77% of missing values), but you can visualize the whole process to fill in these missing values.

Results

This Titanic Jupyter-notebook gave me a score of 0.79425 (which means that it can predict 79.725% of the desired dataset correctly) and put me on the top 19%.

If you consider that there are a lot of cheaters (some of them can get a 100% score, which is verly unlikely in a event like that because random actions can interfer in the survival rate), it is a pretty decent score. Also, you can find the complete datasets with a quickly internet search.

I'm not sharing my final file (submission.csv) to avoid anyone just take it and submit to Kaggle, but you can run the code to get it easily.

titanic-survivors's People

Contributors

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Forkers

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