Exploratory Data Analysis and then predicting cancellations of bookings from a Hotel Bookings Dataset:

Exploratory Data Analysis: A statistical approach to analyze the dataset to summarize the essential information, generally, using visual methods.

• Data Visualisation included:
  • Statistics: Mean, Standard Deviation, Count of various features of the dataset.
  • Barplot for the no. of Cancelled bookings for each hotel type.
  • Barplot for analyzing the month-wise Booking-cancellations
  • Barplot for the peak period of bookings (Month wise)
  • Month wise canceled Bookings
• Correlation between all the variables and the cancellation of the bookings.
• Data Processing:
  • Removed various columns which had enough number of NULL entries.
• Created dummy variables to be used in th prediction model.
• Basic Steps for the model:
  • Split into training and test sets
  • Feature Scaling
  • Trained and predicted using multiple models: Used LogisticRegression and KNearestNeighbors
  • Used sklearn library for the models.
• KNearestNeighbors algorithm stores all the training data and then classifies a new data point based on the similarities.