InputType
- Type of inputs to the prediction engine.OutputType
- Type of outputs to predict from the prediction engine.EvaluatorType
- Type of evaluator produced by the learning algorithm.public class TimeSeriesPredictionLearner<InputType,OutputType,EvaluatorType extends Evaluator<? super InputType,? extends OutputType>> extends AbstractCloneableSerializable implements SupervisedBatchLearner<InputType,OutputType,EvaluatorType>
Modifier and Type | Field and Description |
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static int |
DEFAULT_PREDICTION_HORIZON
Default prediction horizon, 1.
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Constructor and Description |
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TimeSeriesPredictionLearner()
Default constructor
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TimeSeriesPredictionLearner(int predictionHorizon)
Creates a new instance of TimeSeriesPredictionLearner
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TimeSeriesPredictionLearner(int predictionHorizon,
SupervisedBatchLearner<InputType,OutputType,EvaluatorType> supervisedLearner)
Creates a new instance of TimeSeriesPredictionLearner
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Modifier and Type | Method and Description |
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static <InputType,OutputType> |
createPredictionDataset(int predictionHorizon,
java.util.Collection<? extends InputOutputPair<? extends InputType,OutputType>> data)
Creates a dataset that can be used to predict the future by
"predictionHorizon" samples.
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int |
getPredictionHorizon()
Getter for predictionHorizon
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SupervisedBatchLearner<InputType,OutputType,EvaluatorType> |
getSupervisedLearner()
Getter for supervisedLearner
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EvaluatorType |
learn(java.util.Collection<? extends InputOutputPair<? extends InputType,OutputType>> data)
The
learn method creates an object of ResultType using
data of type DataType , using some form of "learning" algorithm. |
void |
setPredictionHorizon(int predictionHorizon)
Setter for predictionHorizon
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void |
setSupervisedLearner(SupervisedBatchLearner<InputType,OutputType,EvaluatorType> supervisedLearner)
Setter for supervisedLearner
|
clone
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
clone
public static final int DEFAULT_PREDICTION_HORIZON
public TimeSeriesPredictionLearner()
public TimeSeriesPredictionLearner(int predictionHorizon)
predictionHorizon
- Number of samples into the future to predict.public TimeSeriesPredictionLearner(int predictionHorizon, SupervisedBatchLearner<InputType,OutputType,EvaluatorType> supervisedLearner)
predictionHorizon
- Number of samples into the future to predict.supervisedLearner
- Learning algorithm that does the heavy lifting.public int getPredictionHorizon()
public void setPredictionHorizon(int predictionHorizon)
predictionHorizon
- Number of samples into the future to predict.public SupervisedBatchLearner<InputType,OutputType,EvaluatorType> getSupervisedLearner()
public void setSupervisedLearner(SupervisedBatchLearner<InputType,OutputType,EvaluatorType> supervisedLearner)
supervisedLearner
- Learning algorithm that does the heavy lifting.public EvaluatorType learn(java.util.Collection<? extends InputOutputPair<? extends InputType,OutputType>> data)
BatchLearner
learn
method creates an object of ResultType
using
data of type DataType
, using some form of "learning" algorithm.learn
in interface BatchLearner<java.util.Collection<? extends InputOutputPair<? extends InputType,OutputType>>,EvaluatorType extends Evaluator<? super InputType,? extends OutputType>>
data
- The data that the learning algorithm will use to create an
object of ResultType
.public static <InputType,OutputType> java.util.ArrayList<InputOutputPair<InputType,OutputType>> createPredictionDataset(int predictionHorizon, java.util.Collection<? extends InputOutputPair<? extends InputType,OutputType>> data)
InputType
- Type of inputs to the prediction engine.OutputType
- Type of outputs to predict from the prediction engine.predictionHorizon
- Number of samples into the future to predict.data
- Data to align for predicting into the future.