In my last post I built a regression model with a single predictor variable. That variable represented the value of a single pixel from a 28×28 image of a hand written digit. In this post I will look at some model variations based on using a larger number of input variables.
In a recent post I created a table that contained two classes of data: images that represent either the handwritten digit ‘5’ or the digit ‘6’. In this post I’ll model the data using logistic regression. I will also take the opportunity to look at the role of training and test datasets, and to highlight the distinction between testing and validation.
If you have ever been to a JMP Discovery Summit or perhaps a JMP user group meeting you will no doubt have come across journal files. The first time you create one can be an unnerving experience since a new journal is simply a blank window. But that is their beauty: they are a blank canvass onto which you can save your JMP output. But more importantly they are a place to capture your thoughts.