Classification Models: Uses three methods to train and test the data, to give overall accuracy scores for future predictions.
Data Analysis: The data analysis folder runs the analysis on the raw data to give an insight on the data set.
Data Imputation: The data imputation folder tests the accuracy of the models, and then uses to impute data.
Prediction model and GUI: the folder contains the code for OLS regression, Elastic Net regression and Decison Trees that were used to try and predict the number of registrations of an event.
Regression models: the folder contains the code for ARIMA, SARIMAX regression and exponetial Smoothing used to forecast the number of bookings.
Time series models: Logistic regression used to predict how many people would be present at an event based on Elastic Net regression that was used for the forecasting. A GUI was used to present these results.