Why neural net models are great at making predictions when the exact nature of the relationship between inputs and the output is not known
In today's post, we explore the use of data mining algorithms in creating a SKU (Stock Keeping Unit) level sales forecast. There are several ways of creating a sales forecast including time series forecasting, simulation and scenario building. Ignoring these methods, we will instead use a neural net model to create a SKU level sales forecast. We will then test the accuracy of the forecast against actual data and try to explain why neural net models are great at at making predictions when the exact nature of the relationship between inputs and the output is not known. This is important because in developing our model, in addition to historical sales data, we will use data about customer demographics as well as unemployment and inflation data. At the outset, while high level conclusions can be drawn about the impact that demographics and other data can have on the sales forecast, the exact nature of the relationship between these inputs (historical sales...