Linear Learner
Use the Linear Learner algorithm to explore a large number of models and choose the
best model that optimizes either continuous objectives, such as mean square error, cross
entropy loss, absolute error, or discrete objectives suited for classification, such as
F1 measure, precision and recall, or accuracy.
When compared with solutions providing a solution to only continuous objectives, the implementation provides a significant increase in speed over naive hyper-parameter optimization techniques.