Spaceship-Titanic
Link : https://www.kaggle.com/competitions/spaceship-titanic/data
Dataset Description
In this competition your task is to predict whether a passenger was transported to an alternate dimension during the Spaceship Titanic’s collision with the spacetime anomaly. To help you make these predictions, you’re given a set of personal records recovered from the ship’s damaged computer system.
File and Data Field Descriptions
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train.csv - Personal records for about two-thirds (~8700) of the passengers, to be used as training data.
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PassengerId
- A unique Id for each passenger. Each Id takes the form gggg_pp where gggg indicates a group the passenger is travelling with and pp is their number within the group. People in a group are often family members, but not always. -
HomePlanet
- The planet the passenger departed from, typically their planet of permanent residence. -
CryoSleep
- Indicates whether the passenger elected to be put into suspended animation for the duration of the voyage. Passengers in cryosleep are confined to their cabins. -
Cabin
- The cabin number where the passenger is staying. Takes the form deck/num/side, where side can be either P for Port or S for Starboard. -
Destination
- The planet the passenger will be debarking to. -
Age
- The age of the passenger. -
VIP
- Whether the passenger has paid for special VIP service during the voyage. -
RoomService
,FoodCourt
,ShoppingMall
,Spa
,VRDeck
- Amount the passenger has billed at each of the Spaceship Titanic’s many luxury amenities. -
Name
- The first and last names of the passenger. -
Transported
- Whether the passenger was transported to another dimension. This is the target, the column you are trying to predict.
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test.csv - Personal records for the remaining one-third (~4300) of the passengers, to be used as test data. Your task is to predict the value of Transported for the passengers in this set.c
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sample_submission.csv
- A submission file in the correct format. -
PassengerId
- Id for each passenger in the test set. -
Transported
- The target. For each passenger, predict either True or False.
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