The dataset used in this project includes quantitative and categorical features from online reviews of 21 hotels located in Las Vegas Strip, extracted from TripAdvisor
The dataset contains 504 records and 20 tuned features, 24 per hotel (two per each month, randomly selected), regarding the year of 2015. The CSV contains a header, with the names of the columns corresponding to the features
Headers corresponding to each column has categorical variables which have text labels but most machine learning algorithms in python accept data with numeric labels only therefore we'll be encoding the categorical variables to numeric labels
Nr.reviews
Nr.hotel reviews
Helpful votes
Traveler type
Swimming Pool
Exercise Room
Basketball Court
Yoga Classes
Club
Free Wifi
Hotel Name
Hotel stars
Nr.rooms
Member years
Using KNN( K-Nearest Neighbours ) is 40.59%
Python
Spyder
Numpy
Panda
Label Encoder
OneHotEncoder