Using Machine Learning to Model Complex Systems

Machine learning techniques help to quickly detect patterns and build accurate predictive models from large data sets. They include neural networks, decision trees, fuzzy logic, K-means clustering, discriminant analysis, and linear, logistic, and nonlinear regression. In this session, see how you can easily compare and evaluate the performance of MATLAB algorithms for machine learning in applications.

Topics include:

• Clustering: segmenting data into natural subgroups
• Classification: building a model to predict groups for new observations
• Regression: building a predictive model from continuous observations