Predictive Modeling and Text Mining

Visit the JMP Online Documentation home page to search for more information on the following topics:

To learn more about creating validation columns, search for "validation column example." For information on other validation options, search for "validation options."
To learn more about fitting classification and regression trees, search for "partition models." For information about advanced tree methods, search for "bootstrap forest" or "boosted tree."
For information on the logworth statistic, search for "splitting criterion."
For information on the construction and interpretation of ROC curves for classification models, search for "ROC curves."
To learn more about fitting neural network models, including the underlying statistical details, search for "neural networks."
To learn more about fitting Generalized Linear Models and Penalized Regression models using Generalized Regression, and the available response distributions, search for "generalized regression models."
To learn more about maximum likelihood estimation in the Generalized Regression platform, search for "estimation method options."
To learn more about comparing competing predictive models using the Model Comparison platform in JMP Pro, search for "model comparison."
To learn more about deploying predictive models using the Formula Depot in JMP Pro, search for "formula depot."
To learn more about processing, exploring and analyzing unstructured text data, search for "Text Explorer."
For information on dimension reduction techniques, such as principal components and cluster analysis, search for "multivariate methods."

For a collection of additional videos, short guides, case studies and materials for learning and teaching predictive modeling in JMP, including recommended books, see the Analytics and Predictive Modeling course materials page.

Search the Resource Center for white papers, book chapters, and articles on a variety of topics related to predictive modeling and data mining.

Explore the Mastering JMP webinar series for additional information on the following topics: