![]() ![]() the value of Transported for the passengers). test file (spaceship_titanic_test.csv) - contains personal records for the remaining one-third (~4300) of the passengers, but not the target variable (i.e.train file (spaceship_titanic_train.csv) - contains personal records of the passengers that would be used to build the machine learning model.This problem is a binary class classification problem where we have to predict which passengers were transported to an alternate dimension or not, and we will be using accuracy as a metric to evaluate our results. Though the ship stayed intact, almost half of the passengers were transported to an alternate dimension! To help rescue crews retrieve the lost passengers, we are challenged to use records recovered from the spaceship’s damaged computer system to predict which passengers were transported to another dimension. Sadly, it met a similar fate as its namesake from 1000 years before. It’s the year 2912 and the interstellar passenger liner Spaceship Titanic has collided with a spacetime anomaly hidden within a dust cloud. ![]() Baseline Model Performance and Model BuildingĪs the first thing, we have to understand the problem.Feature Extraction and Feature Selection.It covers steps to obtain any meaningful insights from the data and to predict the “ground truth” for the test set with an accuracy of ~80% using RandomForestClassifier. This article is a beginner-friendly analysis of the Spaceship Titanic Kaggle Competition. It is designed to be an update of the popular Titanic competition which helps people new to data science learn the basics of machine learning, get acquainted with Kaggle’s platform, and meet others in the community. Kaggle recently launched a fun competition called Spaceship Titanic.
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