Uses of Class
org.hawkular.datamining.forecast.DataPoint

Packages that use DataPoint

Package	Description
org.hawkular.datamining.forecast
org.hawkular.datamining.forecast.models
org.hawkular.datamining.forecast.utils

Uses of DataPoint in org.hawkular.datamining.forecast

Methods in org.hawkular.datamining.forecast that return DataPoint

Modifier and Type	Method and Description
DataPoint	AutomaticForecaster.forecast()
DataPoint	Forecaster.forecast()

Methods in org.hawkular.datamining.forecast that return types with arguments of type DataPoint

Modifier and Type	Method and Description
List<DataPoint>	AutomaticForecaster.forecast(int nAhead)
List<DataPoint>	Forecaster.forecast(int nAhead)

Methods in org.hawkular.datamining.forecast with parameters of type DataPoint

Modifier and Type	Method and Description
void	AutomaticForecaster.learn(DataPoint dataPoint)
void	Forecaster.learn(DataPoint dataPoint)

Method parameters in org.hawkular.datamining.forecast with type arguments of type DataPoint

Modifier and Type	Method and Description
void	AutomaticForecaster.learn(List<DataPoint> dataPoints)
void	Forecaster.learn(List<DataPoint> dataPoints)

Uses of DataPoint in org.hawkular.datamining.forecast.models

Methods in org.hawkular.datamining.forecast.models that return DataPoint

Modifier and Type	Method and Description
DataPoint	ContinuousModel.forecast()
DataPoint	AbstractExponentialSmoothing.forecast()
DataPoint	TimeSeriesModel.forecast() One step ahead prediction

Methods in org.hawkular.datamining.forecast.models that return types with arguments of type DataPoint

Modifier and Type	Method and Description
List<DataPoint>	ContinuousModel.forecast(int nAhead)
List<DataPoint>	AbstractExponentialSmoothing.forecast(int nAhead)
List<DataPoint>	TimeSeriesModel.forecast(int nAhead) Multi step ahead prediction
List<DataPoint>	WeightedMovingAverage.learn()
List<DataPoint>	SimpleMovingAverage.learn()

Methods in org.hawkular.datamining.forecast.models with parameters of type DataPoint

Modifier and Type	Method and Description
int	TimeSeriesModel.TimestampComparator.compare(DataPoint point1, DataPoint point2)
void	ContinuousModel.learn(DataPoint learnData)
void	AbstractExponentialSmoothing.learn(DataPoint dataPoint)
void	TimeSeriesModel.learn(DataPoint learnData) Learn one point
protected abstract void	AbstractExponentialSmoothing.updateState(DataPoint dataPoint)
protected void	TripleExponentialSmoothing.updateState(DataPoint point)
protected void	DoubleExponentialSmoothing.updateState(DataPoint dataPoint)
protected void	SimpleExponentialSmoothing.updateState(DataPoint dataPoint)

Method parameters in org.hawkular.datamining.forecast.models with type arguments of type DataPoint

Modifier and Type	Method and Description
org.apache.commons.math3.optim.nonlinear.scalar.MultivariateFunctionMappingAdapter	DoubleExponentialSmoothing.DoubleExOptimizer.costFunction(List<DataPoint> dataPoints)
org.apache.commons.math3.optim.nonlinear.scalar.MultivariateFunctionMappingAdapter	SimpleExponentialSmoothing.SimpleExOptimizer.costFunction(List<DataPoint> dataPoints)
AccuracyStatistics	ContinuousModel.init(List<DataPoint> learnData)
AccuracyStatistics	AbstractExponentialSmoothing.init(List<DataPoint> dataPoints)
AccuracyStatistics	TimeSeriesModel.init(List<DataPoint> learnData) Initialize model and return statistics - error of one step ahead prediction
protected abstract SimpleExponentialSmoothing.State	AbstractExponentialSmoothing.initState(List<DataPoint> dataPoints)
protected TripleExponentialSmoothing.TripleExState	TripleExponentialSmoothing.initState(List<DataPoint> dataPoints)
protected DoubleExponentialSmoothing.DoubleExState	DoubleExponentialSmoothing.initState(List<DataPoint> initData)
protected SimpleExponentialSmoothing.State	SimpleExponentialSmoothing.initState(List<DataPoint> initData)
static TripleExponentialSmoothing.TripleExState	TripleExponentialSmoothing.initState(List<DataPoint> dataPoints, int periods, MetricContext metricContext)
void	ContinuousModel.learn(List<DataPoint> learnData)
void	AbstractExponentialSmoothing.learn(List<DataPoint> dataPoints)
void	TimeSeriesModel.learn(List<DataPoint> learnData) Learn multiple points
TripleExponentialSmoothing	TripleExponentialSmoothing.TripleExOptimizer.minimizedMSE(List<DataPoint> dataPoints)
DoubleExponentialSmoothing	DoubleExponentialSmoothing.DoubleExOptimizer.minimizedMSE(List<DataPoint> dataPoints)
SimpleExponentialSmoothing	SimpleExponentialSmoothing.SimpleExOptimizer.minimizedMSE(List<DataPoint> dataPoints)
TimeSeriesModel	ModelOptimizer.minimizedMSE(List<DataPoint> trainData)

Constructor parameters in org.hawkular.datamining.forecast.models with type arguments of type DataPoint

Constructor and Description
SimpleMovingAverage(List<DataPoint> dataPoints, int smoothingLength, boolean symmetric)
WeightedMovingAverage(List<DataPoint> dataPoints, double[] weights)

Uses of DataPoint in org.hawkular.datamining.forecast.utils

Methods in org.hawkular.datamining.forecast.utils that return types with arguments of type DataPoint

Modifier and Type	Method and Description
List<DataPoint>	TimeSeriesDecomposition.random()
List<DataPoint>	AdditiveSeasonalDecomposition.random()
List<DataPoint>	TimeSeriesDecomposition.seasonal()
List<DataPoint>	AdditiveSeasonalDecomposition.seasonal()
List<DataPoint>	TimeSeriesDecomposition.trend()
List<DataPoint>	AdditiveSeasonalDecomposition.trend()

Method parameters in org.hawkular.datamining.forecast.utils with type arguments of type DataPoint

Modifier and Type	Method and Description
static int	AutomaticPeriodIdentification.periods(List<DataPoint> data)
static int	AutomaticPeriodIdentification.periods(List<DataPoint> data, double criticalValue)
static double[]	Utils.toArray(List<DataPoint> data) Converts list of data points to array of values

Constructor parameters in org.hawkular.datamining.forecast.utils with type arguments of type DataPoint

Constructor and Description
AdditiveSeasonalDecomposition(List<DataPoint> points, int periods)