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Predicting_Money_Spent_at_Resort

It is From Analytics Vidhya Hackathons, Sponsored by Club Mahindra. It is based on Regression Problem, Where Accuracy matters the most, It is measured by RMSE Score. Different Techniques such as Stacking, Ensembling, Boosting and Scientific Operations such box-cox Operations to reduce skewness of the data.

Description of the columnar attributes

Variable Description

reservation_id : Reservation ID

booking_date : Date of booking

checkin_date : Checkin date recorded at the time of booking

checkout_date : Checkout date recorded at the time of booking

channel_code : Different channels of booking

main_product_code : Type of product a member has purchased

numberofadults : Number of adults travelling

numberofchildren : Number of children travelling

persontravellingid : Type of person travelling

resort_region_code : Resort Region

resort_type_code : Resort Type

room_type_booked_code : Room Type

roomnights : Number of roomnights booked

season_holidayed_code : Season Holidayed

state_code_residence : Residence State of Member

state_code_resort : State in which resort is located

total_pax : Total persons travelling

member_age_buckets : Age bucket of the member

booking_type_code : Type of Booking

memberid : Unique ID of the member

cluster_code : Cluster Code of Resort

reservationstatusid_code : Reservation Status ID

resort_id : Unique Resort ID

amount_spent_per_room_night_scaled : (Target) Resort Spend Per Room Night