Index
All Classes and Interfaces|All Packages|Constant Field Values|Serialized Form
C
- check(List<CheckResultInterface>, TransMeta, StepMeta, RowMetaInterface, String[], String[], RowMetaInterface) - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Check the settings of this step and put findings in a remarks list.
- classifyInstance(Instance) - Method in class org.pentaho.di.scoring.WekaScoringModel
-
Return a classification.
- classifyInstances(Instances) - Method in class org.pentaho.di.scoring.WekaScoringModel
-
Batch scoring method.
- clone() - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Clone this step's meta data
- createScorer(Object) - Static method in class org.pentaho.di.scoring.WekaScoringModel
-
Static factory method to create an instance of an appropriate subclass of WekaScoringModel given a Weka model.
D
- DEFAULT_BATCH_SCORING_SIZE - Static variable in class org.pentaho.di.scoring.WekaScoringMeta
-
Batch scoring size
- deSerializeBase64Model(String) - Method in class org.pentaho.di.scoring.WekaScoringMeta
- distributionForInstance(Instance) - Method in class org.pentaho.di.scoring.WekaScoringModel
-
Return a probability distribution (over classes or clusters).
- distributionsForInstances(Instances) - Method in class org.pentaho.di.scoring.WekaScoringModel
-
Batch scoring method.
- done() - Method in class org.pentaho.di.scoring.WekaScoringModel
-
Tell the model that this scoring run is finished.
E
- equals(Object) - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Check for equality
F
- findMappings(Instances, RowMetaInterface) - Static method in class org.pentaho.di.scoring.WekaScoringData
-
Finds a mapping between the attributes that a Weka model has been trained with and the incoming Kettle row format.
G
- generatePrediction(RowMetaInterface, RowMetaInterface, Object[], WekaScoringMeta) - Method in class org.pentaho.di.scoring.WekaScoringData
-
Generates a prediction (more specifically, an output row containing all input Kettle fields plus new fields that hold the prediction(s)) for an incoming Kettle row given a Weka model.
- generatePredictions(RowMetaInterface, RowMetaInterface, List<Object[]>, WekaScoringMeta) - Method in class org.pentaho.di.scoring.WekaScoringData
-
Generates a batch of predictions (more specifically, an array of output rows containing all input Kettle fields plus new fields that hold the prediction(s)) for each incoming Kettle row given a Weka model.
- getBatchScoringSize() - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Get the batch size to use if the model is a batch scoring model
- getCacheLoadedModels() - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Get whether to cache loaded models in memory
- getData() - Method in class org.pentaho.di.scoring.WekaScoringDialog
-
Grab data out of the step meta object
- getDefaultModel() - Method in class org.pentaho.di.scoring.WekaScoringData
-
Get the default model for this copy of the step to use.
- getDefaultModel() - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Gets the default model (only used when model file names are being sourced from a field in the incoming rows).
- getDialogClassName() - Method in class org.pentaho.di.scoring.WekaScoringMeta
- getFieldNameToLoadModelFrom() - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Get the name of the incoming field that holds paths to model files
- getFields(RowMetaInterface, String, RowMetaInterface[], StepMeta, VariableSpace) - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Generates row meta data to represent the fields output by this step
- getFileNameFromField() - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Get whether filename is coming from an incoming field
- getHeader() - Method in class org.pentaho.di.scoring.WekaScoringModel
-
Get the header of the Instances that was used build this Weka model
- getModel() - Method in class org.pentaho.di.scoring.WekaScoringData
-
Get the model that this copy of the step is using
- getModel() - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Get the Weka model
- getModel() - Method in class org.pentaho.di.scoring.WekaScoringModel
-
Get the weka model
- getOutputProbabilities() - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Get whether to predict probabilities
- getOutputRowMeta() - Method in class org.pentaho.di.scoring.WekaScoringData
-
Get the meta data for the output format
- getSavedModelFileName() - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Get the file name that the incrementally updated model will be saved to when the current stream of data terminates
- getSerializedModelFileName() - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Get the filename of the serialized Weka model to load/import from
- getStep(StepMeta, StepDataInterface, int, TransMeta, Trans) - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Get the executing step, needed by Trans to launch a step.
- getStepData() - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Get a new instance of the appropriate data class.
- getStoreModelInStepMetaData() - Method in class org.pentaho.di.scoring.WekaScoringMeta
- getUpdateIncrementalModel() - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Get whether the model is to be incrementally updated with each incoming row (after making a prediction for it).
- getXML() - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Return the XML describing this (configured) step
- getXML(boolean) - Method in class org.pentaho.di.scoring.WekaScoringMeta
H
- hashCode() - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Hash code method
I
- init(StepMetaInterface, StepDataInterface) - Method in class org.pentaho.di.scoring.WekaScoring
-
Initialize the step.
- isBatchPredictor() - Method in class org.pentaho.di.scoring.WekaScoringModel
-
Returns true if the encapsulated Weka model can produce predictions in a batch.
- isSupervisedLearningModel() - Method in class org.pentaho.di.scoring.WekaScoringModel
-
Returns true if the encapsulated Weka model is a supervised model (i.e.
- isUpdateableModel() - Method in class org.pentaho.di.scoring.WekaScoringModel
-
Returns true if the encapsulated Weka model can be updated incrementally in an instance by instance fashion.
L
- loadModelFile() - Method in class org.pentaho.di.scoring.WekaScoringMeta
- loadSerializedModel(String, LogChannelInterface, VariableSpace) - Static method in class org.pentaho.di.scoring.WekaScoringData
-
Loads a serialized model.
- loadXML(Node, List<DatabaseMeta>, Map<String, Counter>) - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Loads the meta data for this (configured) step from XML.
- LogAdapter - Class in org.pentaho.di.scoring
-
Adapts Kettle logging to Weka's Logger interface
- LogAdapter(LogChannelInterface) - Constructor for class org.pentaho.di.scoring.LogAdapter
- logMessage(String) - Method in class org.pentaho.di.scoring.LogAdapter
M
- m_defaultModel - Variable in class org.pentaho.di.scoring.WekaScoringData
-
Holds a default model - only used when model files are sourced from a field in the incoming data rows.
- m_model - Variable in class org.pentaho.di.scoring.WekaScoringData
-
Holds the actual Weka model (classifier, clusterer or PMML) used by this copy of the step
- m_outputRowMeta - Variable in class org.pentaho.di.scoring.WekaScoringData
-
the output data format
- m_updateIncrementalModel - Variable in class org.pentaho.di.scoring.WekaScoringData
-
whether to update the model (if incremental)
- mapIncomingRowMetaData(Instances, RowMetaInterface, boolean, LogChannelInterface) - Method in class org.pentaho.di.scoring.WekaScoringData
-
Finds a mapping between the attributes that a Weka model has been trained with and the incoming Kettle row format.
- modelFileExists(String, VariableSpace) - Static method in class org.pentaho.di.scoring.WekaScoringData
N
- NO_MATCH - Static variable in class org.pentaho.di.scoring.WekaScoringData
-
some constants for various input field - attribute match/type problems
O
- onEnvironmentInit() - Method in class org.pentaho.di.scoring.WekaScoringLifecycleListener
- onEnvironmentShutdown() - Method in class org.pentaho.di.scoring.WekaScoringLifecycleListener
- open() - Method in class org.pentaho.di.scoring.WekaScoringDialog
-
Open the dialog
- org.pentaho.di.scoring - package org.pentaho.di.scoring
- outputBatchRows() - Method in class org.pentaho.di.scoring.WekaScoring
P
- PKG - Static variable in class org.pentaho.di.scoring.WekaScoringMeta
- processRow(StepMetaInterface, StepDataInterface) - Method in class org.pentaho.di.scoring.WekaScoring
-
Process an incoming row of data.
R
- readRep(Repository, ObjectId, List<DatabaseMeta>, Map<String, Counter>) - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Read this step's configuration from a repository
S
- saveRep(Repository, ObjectId, ObjectId) - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Save this step's meta data to a repository
- saveSerializedModel(WekaScoringModel, File) - Static method in class org.pentaho.di.scoring.WekaScoringData
- setBatchScoringSize(String) - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Set the batch size to use if the model is a batch scoring model
- setCacheLoadedModels(boolean) - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Set whether to cache loaded models in memory
- setDefault() - Method in class org.pentaho.di.scoring.WekaScoringMeta
- setDefaultModel(WekaScoringModel) - Method in class org.pentaho.di.scoring.WekaScoringData
-
Set the default model for this copy of the step to use.
- setDefaultModel(WekaScoringModel) - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Sets the default model (only used when model file names are being sourced from a field in the incoming rows).
- setFieldNameToLoadModelFrom(String) - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Set the name of the incoming field that holds paths to model files
- setFileNameFromField(boolean) - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Set whether filename is coming from an incoming field
- setHeader(Instances) - Method in class org.pentaho.di.scoring.WekaScoringModel
-
Set the Instances header
- setLog(LogChannelInterface) - Method in class org.pentaho.di.scoring.WekaScoringModel
-
Set the log to pass on to the model.
- setModel(Object) - Method in class org.pentaho.di.scoring.WekaScoringModel
-
Set the weka model
- setModel(WekaScoringModel) - Method in class org.pentaho.di.scoring.WekaScoringData
-
Set the model for this copy of the step to use
- setModel(WekaScoringModel) - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Set the Weka model
- setOutputProbabilities(boolean) - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Set whether to predict probabilities
- setOutputRowMeta(RowMetaInterface) - Method in class org.pentaho.di.scoring.WekaScoringData
-
Set the meta data for the output format
- setSavedModelFileName(String) - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Set the file name that the incrementally updated model will be saved to when the current stream of data terminates
- setSerializedModelFileName(String) - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Set the file name of the serialized Weka model to load/import from
- setStoreModelInStepMetaData(boolean) - Method in class org.pentaho.di.scoring.WekaScoringMeta
- setUpdateIncrementalModel(boolean) - Method in class org.pentaho.di.scoring.WekaScoringMeta
-
Set whether to update the model incrementally
- statusMessage(String) - Method in class org.pentaho.di.scoring.LogAdapter
T
- TYPE_MISMATCH - Static variable in class org.pentaho.di.scoring.WekaScoringData
U
- update(Instance) - Method in class org.pentaho.di.scoring.WekaScoringModel
-
Update (if possible) a model with the supplied Instance
W
- WekaScoring - Class in org.pentaho.di.scoring
-
Applies a pre-built weka model (classifier or clusterer) to incoming rows and appends predictions.
- WekaScoring(StepMeta, StepDataInterface, int, TransMeta, Trans) - Constructor for class org.pentaho.di.scoring.WekaScoring
-
Creates a new
WekaScoring
instance. - WekaScoringData - Class in org.pentaho.di.scoring
-
Holds temporary data and has routines for loading serialized models.
- WekaScoringData() - Constructor for class org.pentaho.di.scoring.WekaScoringData
- WekaScoringDialog - Class in org.pentaho.di.scoring
-
The UI class for the WekaScoring transform
- WekaScoringDialog(Shell, Object, TransMeta, String) - Constructor for class org.pentaho.di.scoring.WekaScoringDialog
- WekaScoringLifecycleListener - Class in org.pentaho.di.scoring
- WekaScoringLifecycleListener() - Constructor for class org.pentaho.di.scoring.WekaScoringLifecycleListener
- WekaScoringMeta - Class in org.pentaho.di.scoring
-
Contains the meta data for the WekaScoring step.
- WekaScoringMeta() - Constructor for class org.pentaho.di.scoring.WekaScoringMeta
-
Creates a new
WekaScoringMeta
instance. - WekaScoringModel - Class in org.pentaho.di.scoring
-
Abstract wrapper class for a Weka model.
- WekaScoringModel(Object) - Constructor for class org.pentaho.di.scoring.WekaScoringModel
-
Creates a new
WekaScoringModel
instance.
X
- XML_TAG - Static variable in class org.pentaho.di.scoring.WekaScoringMeta
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