PREDICTING TITANIC SURVIVAL WITH LOGISTIC REGRESSION: A MACHINE LEARNING APPROACH
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Abstract
The sinking of RMS Titanic is one of the most infamous and disastrous shipwrecks ever. During it’s voyage and early morning hours of April 15, 1912, the Titanic sank after colliding with an iceberg, killing an approximate of 1502 passengers and crew out of 2224 making it one of many of the deadliest commercial maritime in history. The entire world was deeply shocked and saddened after hearing the news of this disaster which resulted in improved ship safety legislation. It’s architect, Thomas Andrews died in the disaster. An observation that came forth from the sinking of Titanic is the fact that certain individuals had a better chance at living than the others. Kids and women had been given the most priority. Social classes were heavily stratified in the early twentieth century, this was especially implemented on the Titanic Firstly, the goal is use and apply exploratory data analytics (EDA) to uncover previously hidden facts in the data set available. Then the task is to later apply various machine learning models to conclude the study of who has a better chance of surviving this disaster. The outcomes of application of the different machine learning models were then set side by side and analyzed based upon precision
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