Supervised Machine Learning - Multiple Linear Regression
Now the dataset has been created, the next step is to produce a predictive model.
In this case a "Supervised Machine Learning" model will be used. This is where you have input variables (X) and an output variable (Y), and an algorithm is used to learn the relationship between the input variables and the output variable. The specific algorithm to be used initially here, is known as Multiple Linear Regression.
The exact definition of "Multiple Linear Regression" is as follows :-
Multiple linear regression (MLR) is a statistical technique that uses several explanatory variables to predict the outcome of a response variable.
The goal of multiple linear regression (MLR) is to model the relationship between the explanatory and response variables.
The 'response' variable is the Attendance of a soccer match, with all the remaining features in the dataset being the explanatory variables.
The code (ipython notebook), can be found in my github repo, here.