In this webinar, you will learn how to do data driven fitting with MathWorks products.
Data driven fitting derives all of the information required to generate a model directly from the data set. Data driven fitting is also referred to as “black box” modeling and nonparametric fitting.
Applied examples from the webinar include:
- Comparing the accuracy of different fitting techniques
- Using back-testing to measure the accuracy of your model
- Generating confidence intervals with bootstrap
- Using cross validation to avoid overfitting
Key analytical techniques include:
- Neural Networks
- Boosted and bagged decision trees
- Localized regression
- Smoothing splines
View the MATLAB code
About the Presenter: Richard Willey is a product marketing manager focused on MATLAB and add-on products for data analysis, statistics, and curve fitting. Prior to joining MathWorks in 2007, Richard worked at Wind River Systems and Symantec. Richard has a dual masters in engineering and management from the Massachusetts Institute of Technology and a master’s degree in economics from Indiana University.
