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.
- Clustering: segmenting data into natural subgroups
- Classification: building a model to predict groups for new observations
- Regression: building a predictive model from continuous observations
Recorded: 1 Aug 2013
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