Unlike commercial data mining applications in finance, retail, and telecommunications, data sets from life science domains typically have orders of magnitude more predictors than observations. In these “wide data” instances, it is very easy to overfit the data with predictive models. Furthermore, it is rarely obvious what form of predictive model will be best for a new data set.

Consequently, honest cross validation model comparison is essential to achieve some assurance of generalizability and optimality. We will introduce the predictive modeling capabilities of JMP Clinical and JMP Genomics.

During this webinar, you will learn:

  • techniques for reducing the predictor space
  • tools for comparing a large pool of potential models to find the best ones for a given data set
  • drill-down actions for determining the usefulness of a particular model.

Data from a clinical trial of aneurysmal subarachnoid hemorrhage and a genomics study using next generation sequencing will provide illustration.

Download the Step-by-Step Guide

Register now for this free Webinar.

  Please subscribe me to JMP Newswire, the monthly newsletter for JMP users.
  Yes, you may send me emails occasionally about JMP products and services. I understand that I can withdraw my consent at any time by clicking the opt-out link in the emails.

JMP Statistical Discovery LLC. Your information will be handled in accordance with our Privacy Statement.