Category Archives: Modelling

Segmented Regression

I’m sure there is a more technically correct term for this: I use the phrase segmented regression to describe the process whereby I select a segment of data within a curve and build a regression model for just that segment.

click on the image to see an animated view
click on the image to see an animated view

I have some code to aid the process.  The code illustrates how to perform regression on-the-fly as well as how to utilise the MouseTrap function to handle mouse movement events.

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Stepping Carefully

In this post I will continue with my so-called hieroglyphics project.  This project uses a set of image data that describes handwritten characters.  The dataset is frequently used to evaluate machine-learning algorithms.  I’m using the dataset to explore a variety of modelling techniques within JMP.

In my last post I used a script to incrementally add terms to my model so that I could explore the performance of the model with increasing complexity.  But the order in which I added the terms was based on a heuristic and it wasn’t necessarily optimal.  So in this post I want to explore using stepwise regression.

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Logistic Regression pt.1

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.

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