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What is Cluster-Weighted Modeling Explained about?

Cluster-weighted modeling (CWM) is an algorithmic approach for nonlinear prediction of outputs from inputs based on density estimation using multiple models, each appropriate for a sub-region of the input space. CWM works in joint input-output space by constructing a probability density function from which predictions are obtained. The density function is a mixture model consisting of weighted clusters, with each cluster having its own conditional density relating inputs to outputs for that region. CWM can

Author

john949

Language

EN