InputType
- The type of input data in the input-output pair that
the learner can learn from. The Evaluator
learned from the
algorithm also takes this as the input parameter.OutputType
- The type of output data in the input-output pair that
the learner can learn from. The Evaluator
learned from the
algorithm also produces this as its output.ResultType
- The type of object created by the learning algorithm.
For example, a LinearBinaryCategorizer
.public interface SupervisedIncrementalLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> extends IncrementalLearner<InputOutputPair<? extends InputType,OutputType>,ResultType>
InputOutputPair
.Modifier and Type | Method and Description |
---|---|
void |
update(ResultType target,
InputType input,
OutputType output)
The
update method updates an object of ResultType using
the given a new supervised input-output pair, using some form of
"learning" algorithm. |
createInitialLearnedObject, update, update
clone
void update(ResultType target, InputType input, OutputType output)
update
method updates an object of ResultType
using
the given a new supervised input-output pair, using some form of
"learning" algorithm.target
- The object to update.input
- The supervised input to learn from.output
- The supervised output to learn from.