Package | Description |
---|---|
org.elasticsearch.search.aggregations.pipeline.movavg | |
org.elasticsearch.search.aggregations.pipeline.movavg.models |
Modifier and Type | Method and Description |
---|---|
static MovAvgModel |
SimulatedAnealingMinimizer.minimize(MovAvgModel model,
com.google.common.collect.EvictingQueue<Double> train,
double[] test)
Runs the simulated annealing algorithm and produces a model with new coefficients that, theoretically
fit the data better and generalizes to future forecasts without overfitting.
|
Modifier and Type | Method and Description |
---|---|
static MovAvgModel |
SimulatedAnealingMinimizer.minimize(MovAvgModel model,
com.google.common.collect.EvictingQueue<Double> train,
double[] test)
Runs the simulated annealing algorithm and produces a model with new coefficients that, theoretically
fit the data better and generalizes to future forecasts without overfitting.
|
Constructor and Description |
---|
MovAvgPipelineAggregator.Factory(String name,
String[] bucketsPaths,
ValueFormatter formatter,
BucketHelpers.GapPolicy gapPolicy,
int window,
int predict,
MovAvgModel model,
boolean minimize) |
MovAvgPipelineAggregator(String name,
String[] bucketsPaths,
ValueFormatter formatter,
BucketHelpers.GapPolicy gapPolicy,
int window,
int predict,
MovAvgModel model,
boolean minimize,
Map<String,Object> metadata) |
Modifier and Type | Class and Description |
---|---|
class |
EwmaModel
Calculate a exponentially weighted moving average
|
class |
HoltLinearModel
Calculate a doubly exponential weighted moving average
|
class |
HoltWintersModel
Calculate a triple exponential weighted moving average
|
class |
LinearModel
Calculate a linearly weighted moving average, such that older values are
linearly less important.
|
class |
SimpleModel
Calculate a simple unweighted (arithmetic) moving average
|
Modifier and Type | Method and Description |
---|---|
MovAvgModel |
HoltWintersModel.clone() |
abstract MovAvgModel |
MovAvgModel.clone()
Clone the model, returning an exact copy
|
MovAvgModel |
HoltLinearModel.clone() |
MovAvgModel |
LinearModel.clone() |
MovAvgModel |
SimpleModel.clone() |
MovAvgModel |
EwmaModel.clone() |
MovAvgModel |
HoltWintersModel.neighboringModel() |
abstract MovAvgModel |
MovAvgModel.neighboringModel()
Generates a "neighboring" model, where one of the tunable parameters has been
randomly mutated within the allowed range.
|
MovAvgModel |
HoltLinearModel.neighboringModel() |
MovAvgModel |
LinearModel.neighboringModel() |
MovAvgModel |
SimpleModel.neighboringModel() |
MovAvgModel |
EwmaModel.neighboringModel() |
MovAvgModel |
HoltWintersModel.HoltWintersModelParser.parse(Map<String,Object> settings,
String pipelineName,
int windowSize,
ParseFieldMatcher parseFieldMatcher) |
abstract MovAvgModel |
MovAvgModel.AbstractModelParser.parse(Map<String,Object> settings,
String pipelineName,
int windowSize,
ParseFieldMatcher parseFieldMatcher)
Parse a settings hash that is specific to this model
|
MovAvgModel |
HoltLinearModel.DoubleExpModelParser.parse(Map<String,Object> settings,
String pipelineName,
int windowSize,
ParseFieldMatcher parseFieldMatcher) |
MovAvgModel |
LinearModel.LinearModelParser.parse(Map<String,Object> settings,
String pipelineName,
int windowSize,
ParseFieldMatcher parseFieldMatcher) |
MovAvgModel |
SimpleModel.SimpleModelParser.parse(Map<String,Object> settings,
String pipelineName,
int windowSize,
ParseFieldMatcher parseFieldMatcher) |
MovAvgModel |
EwmaModel.SingleExpModelParser.parse(Map<String,Object> settings,
String pipelineName,
int windowSize,
ParseFieldMatcher parseFieldMatcher) |
static MovAvgModel |
MovAvgModelStreams.read(StreamInput in) |
MovAvgModel |
MovAvgModelStreams.Stream.readResult(StreamInput in) |
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