Page History

...

1. Auto-detect: In this method, specific types are associated with classification and regression. Common types for classification are boolean and text. Common types for regression are double precision and other numeric types.
   It is unclear on the best type for integer response type. It is recommended to treat it like a classification task, with the option to cast it to double precision if regression is desired.
   Example of this method is tree_trainapproach are decision tree and random forest.

2. Separate functions: An alternative method is to create separate functions for the classification and regression tasks. Best example for this is ‘svm_classification’ and ‘svm_regression’. Examples of this approach are SVM and MLP.  This method works best if the two forms of functions have different set of parameters.

3. Parameter to differentiate: A parameter could be used to distinguish between the tasks, with the response variable either cast to appropriate forms (eg. boolean cast to integer for regression or double precision cast to integer for classification). Currently MADlib does not include a function using this method.

...