Build the Predictive Model

We have now gathered our data and cleansed/transformed it to suit our modeling needs. The next step is to actually build the model. The goal of predictive modeling is to build a model to predict the future outcomes using statistical techniques.

We use well-known statistical methods (algorithms) to find the function (model) that best describes a dependency between different variables (a.k.a features). The crux of this is to fit a model to the data such that the function we get is able to predict the outcome based on the given features. In our example, Account Balance, Loan Purpose, Telephone, etc are all predictors/features. The creditability is the outcome/response (the value that we are trying to predict). This is also called the target class, response variable or dependent variable.