TimeSeriesRegressionPredictorImpl (API for com.datarobot:datarobot-prediction 2.1.6)

java.lang.Object
- com.datarobot.prediction.TimeSeriesBase
- - com.datarobot.prediction.TimeSeriesRegressionPredictorImpl

All Implemented Interfaces:

IEventProvider<TimeSeriesRegressionScoreEventInfo>, IPredictorInfo, ITimeSeriesModelInfo, ITimeSeriesRegressionPredictor, Serializable
```
public class TimeSeriesRegressionPredictorImpl
extends TimeSeriesBase
implements ITimeSeriesRegressionPredictor
```
See Also:

Serialized Form

Field Summary

Fields
Modifier and Type	Field and Description
`protected LinkedHashMap<String,Class>`	`features`
`protected Map<String,Integer>`	`featuresIndexes`
`protected String`	`modelId`
`protected Map<String,String>`	`modelInfo`
`protected int`	`numDoubles`
`protected int`	`numStrings`
`protected ConcurrentHashMap<String,String>`	`sanitizedFeaturesCache`
`protected com.datarobot.prediction.PredictorBase.GenericEvent<ScoreEventT>`	`scoreEvent`
`protected String`	`targetName`

Fields inherited from class com.datarobot.prediction.TimeSeriesBase
dateColumnName, dateFormat, fdw, fw, seriesIdColumnName, timeStep

Constructor Summary

Constructors
Modifier Constructor and Description

protected TimeSeriesRegressionPredictorImpl(TimeSeriesPredictor predictor)

Constructors
Modifier	Constructor and Description
`protected`	`TimeSeriesRegressionPredictorImpl(TimeSeriesPredictor predictor)`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`protected Row`	`extractFeatures(Iterable<?> row)`
`protected Row`	`extractFeatures(Map<String,?> row)` Extracts features that are needed from initial row.
`protected Map<String,?>`	`extractFeaturesMap(Iterable<?> row)`
`String`	`getDateColumnName()` Getter for Date Column Name.
`String`	`getDateFormat()` Expected date format for the input dates.
`protected String`	`getDefaultEmptyCollumnName()` Return label for empty column.
`protected Set<String>`	`getDoubleMissingValuesLabels()` Returns the set of null labels.
`protected Double`	`getDoubleValue(String featureName, Object value)` Replaces double missing value with NaN.
`Map.Entry<Integer,Integer>`	`getFeatureDerivationWindow()` Getter for Feature Derivation Interval (FDW).
`LinkedHashMap<String,Class>`	`getFeatures()` Model specific features that are required for scoring.
`protected Field`	`getField(Class clazz, String fieldName)`
`Map.Entry<Integer,Integer>`	`getForecastWindow()` Getter for Forecast Interval.
`String`	`getModelId()` DataRobot Model ID.
`Class<?>`	`getPredictorClass()` What the type of the model
`Event<TimeSeriesRegressionScoreEventInfo>`	`getScoreEvent()` Returns the event that is invoked for each of the score calculated by the model.
`String`	`getSeriesIdColumnName()` Getter for Series ID Column Name.
`Map.Entry<Integer,String>`	`getTimeStep()` Getter for Time Step.
`protected Map<String,String>`	`initializeModelInfo(PredictorT predictor)`
`protected String`	`sanitize(String name)` Some pre-processing for feature name.
`List<TimeSeriesScore<Double>>`	`score(ArrayList<Map<String,?>> rows)` Calculates score for the Time-Series `rows`.
`List<TimeSeriesScore<Double>>`	`score(ArrayList<Map<String,?>> rows, String forecastPoint)` Calculates score for the Time-Series `rows`.
`List<TimeSeriesScore<Double>>`	`score(ArrayList<Map<String,?>> rows, String startDate, String endDate)` Calculates historical scores for the Time-Series `rows`.
`protected void`	`sendScoreInfo(ScoreEventT eventInfo)`

Methods inherited from class com.datarobot.prediction.TimeSeriesBase
extractRows

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - numDoubles
```
protected int numDoubles
```
  - numStrings
```
protected int numStrings
```
  - features
```
protected LinkedHashMap<String,Class> features
```
  - featuresIndexes
```
protected Map<String,Integer> featuresIndexes
```
  - sanitizedFeaturesCache
```
protected ConcurrentHashMap<String,String> sanitizedFeaturesCache
```
  - modelInfo
```
protected Map<String,String> modelInfo
```
  - modelId
```
protected String modelId
```
  - targetName
```
protected String targetName
```
  - scoreEvent
```
protected final com.datarobot.prediction.PredictorBase.GenericEvent<ScoreEventT extends EventInfo> scoreEvent
```
- Constructor Detail
  - TimeSeriesRegressionPredictorImpl
```
protected TimeSeriesRegressionPredictorImpl(TimeSeriesPredictor predictor)
```
- Method Detail
  - score
```
public List<TimeSeriesScore<Double>> score(ArrayList<Map<String,?>> rows)
```
    Description copied from interface: ITimeSeriesRegressionPredictor
    
    Calculates score for the Time-Series rows. NOTE: rows will be sorted lexicographical order by series_id then by date so adds linear overhead if all data is already sorted and historic data is extracted from the rows to predict by the setted/unsetted to not NaN target values.
    
    Specified by:
    
    score in interface ITimeSeriesRegressionPredictor
    
    Parameters:
    
    rows - time-series that contains both historic data and points to predict.
    
    Returns:
    
    collection of scores only for the rows to predict.
  - score
```
public List<TimeSeriesScore<Double>> score(ArrayList<Map<String,?>> rows,
                                           String forecastPoint)
```
    Description copied from interface: ITimeSeriesRegressionPredictor
    
    Calculates score for the Time-Series rows. NOTE: rows will be sorted lexicographical order by series_id then by date so adds linear overhead if all data is already sorted. Historic data is extracted from the rows to predict by the forecastPoint.
    
    Specified by:
    
    score in interface ITimeSeriesRegressionPredictor
    
    Parameters:
    
    rows - time-series that contains both historic data and points to predict.
    
    forecastPoint - date from which to start predictions.
    
    Returns:
    
    collection of scores only for the rows to predict.
  - score
```
public List<TimeSeriesScore<Double>> score(ArrayList<Map<String,?>> rows,
                                           String startDate,
                                           String endDate)
```
    Description copied from interface: ITimeSeriesRegressionPredictor
    
    Calculates historical scores for the Time-Series rows. NOTE: rows is expected to be sorted by the date, and contains only historic data.
    
    Specified by:
    
    score in interface ITimeSeriesRegressionPredictor
    
    Parameters:
    
    rows - history time-series.
    
    startDate - start date for historical predictions.
    
    endDate - end date for historical predictions.
    
    Returns:
    
    collection of scores only for the rows between startDate and endDate.
  - getSeriesIdColumnName
```
public String getSeriesIdColumnName()
```
    Description copied from interface: ITimeSeriesModelInfo
    
    Getter for Series ID Column Name.
    
    Specified by:
    
    getSeriesIdColumnName in interface ITimeSeriesModelInfo
    
    Returns:
    
    series id used during training.
  - getDateColumnName
```
public String getDateColumnName()
```
    Description copied from interface: ITimeSeriesModelInfo
    
    Getter for Date Column Name.
    
    Specified by:
    
    getDateColumnName in interface ITimeSeriesModelInfo
    
    Returns:
    
    date column name used for indexing.
  - getTimeStep
```
public Map.Entry<Integer,String> getTimeStep()
```
    Description copied from interface: ITimeSeriesModelInfo
    
    Getter for Time Step. Pair of quantity to time unit. Time Unit could be: - ROW - MILLISECOND - SECOND - MINUTE - HOUR - DAY - WEEK - MONTH - QUARTER - YEAR
    
    Specified by:
    
    getTimeStep in interface ITimeSeriesModelInfo
    
    Returns:
    
    time step used for the time series processing.
  - getFeatureDerivationWindow
```
public Map.Entry<Integer,Integer> getFeatureDerivationWindow()
```
    Description copied from interface: ITimeSeriesModelInfo
    
    Getter for Feature Derivation Interval (FDW). See documentation https://app.datarobot.com/docs/time/time-series.html#framework Pair of min units number and max units number. So window is calculated date based formulas similar to: [ forecast_point - max * time_step_millis, forecast_point - min * time_step_millis ]
    
    Specified by:
    
    getFeatureDerivationWindow in interface ITimeSeriesModelInfo
    
    Returns:
    
    feature derivation window used for feature extraction.
  - getForecastWindow
```
public Map.Entry<Integer,Integer> getForecastWindow()
```
    Description copied from interface: ITimeSeriesModelInfo
    
    Getter for Forecast Interval. Pair of min units number and max units number So window is calculated date based formulas similar to: [ forecast_point + min * time_step_millis, forecast_point + max * time_step_millis ]
    
    Specified by:
    
    getForecastWindow in interface ITimeSeriesModelInfo
    
    Returns:
    
    feature derivation window used for feature extraction.
  - getDateFormat
```
public String getDateFormat()
```
    Description copied from interface: ITimeSeriesModelInfo
    
    Expected date format for the input dates.
    
    Specified by:
    
    getDateFormat in interface ITimeSeriesModelInfo
    
    Returns:
    
    date format.
  - getModelId
```
public String getModelId()
```
    Description copied from interface: IPredictorInfo
    
    DataRobot Model ID.
    
    Specified by:
    
    getModelId in interface IPredictorInfo
    
    Returns:
    
    string model id.
  - getFeatures
```
public LinkedHashMap<String,Class> getFeatures()
```
    Description copied from interface: IPredictorInfo
    
    Model specific features that are required for scoring. The order of entries is important.
    
    Specified by:
    
    getFeatures in interface IPredictorInfo
    
    Returns:
    
    Map of feature names and expected type in the order.
  - getPredictorClass
```
public Class<?> getPredictorClass()
```
    Description copied from interface: IPredictorInfo
    
    What the type of the model
    
    Specified by:
    
    getPredictorClass in interface IPredictorInfo
    
    Returns:
    
    interface class that implements that particular model.
  - getScoreEvent
```
public Event<TimeSeriesRegressionScoreEventInfo> getScoreEvent()
```
    Description copied from interface: IEventProvider
    
    Returns the event that is invoked for each of the score calculated by the model.
    
    Specified by:
    
    getScoreEvent in interface IEventProvider<TimeSeriesRegressionScoreEventInfo>
    
    Returns:
    
    scoring event information.
  - extractFeatures
```
protected Row extractFeatures(Map<String,?> row)
```
    Extracts features that are needed from initial row.
    
    Parameters:
    
    row - - Map of initial feature name to its value.
    
    Returns:
    
    - internal type for scoring.
  - extractFeatures
```
protected Row extractFeatures(Iterable<?> row)
```
  - extractFeaturesMap
```
protected Map<String,?> extractFeaturesMap(Iterable<?> row)
```
  - sanitize
```
protected String sanitize(String name)
```
    Some pre-processing for feature name.
    
    Parameters:
    
    name - - original feature name.
    
    Returns:
    
    - sanitized name.
  - getDoubleValue
```
protected Double getDoubleValue(String featureName,
                                Object value)
```
    Replaces double missing value with NaN.
    
    Parameters:
    
    featureName - - name of the feature.
    
    value - - object feature value.
    
    Returns:
    
    - parsed Double value.
  - getDefaultEmptyCollumnName
```
protected String getDefaultEmptyCollumnName()
```
    Return label for empty column.
    
    Returns:
    
    - empty column name.
  - getDoubleMissingValuesLabels
```
protected Set<String> getDoubleMissingValuesLabels()
```
    Returns the set of null labels.
    
    Returns:
    
    - set of null labels.
  - getField
```
protected Field getField(Class clazz,
                         String fieldName)
```
  - initializeModelInfo
```
protected Map<String,String> initializeModelInfo(PredictorT predictor)
```
  - sendScoreInfo
```
protected void sendScoreInfo(ScoreEventT eventInfo)
```

Class TimeSeriesRegressionPredictorImpl

Field Summary

Fields inherited from class com.datarobot.prediction.TimeSeriesBase

Constructor Summary

Method Summary

Methods inherited from class com.datarobot.prediction.TimeSeriesBase

Methods inherited from class java.lang.Object

Field Detail

numDoubles

numStrings

features

featuresIndexes

sanitizedFeaturesCache

modelInfo

modelId

targetName

scoreEvent

Constructor Detail

TimeSeriesRegressionPredictorImpl

Method Detail

score

score

score

getSeriesIdColumnName

getDateColumnName

getTimeStep

getFeatureDerivationWindow

getForecastWindow

getDateFormat

getModelId

getFeatures

getPredictorClass

getScoreEvent

extractFeatures

extractFeatures

extractFeaturesMap

sanitize

getDoubleValue

getDefaultEmptyCollumnName

getDoubleMissingValuesLabels

getField

initializeModelInfo

sendScoreInfo