public class WekaClassifier extends BaseClassifier implements WekaModel, Citable
Example: model = new models.classification.WekaClassifier trees.REPTree -L 5
Usage: <Weka classifier> [<classifier options...>]
| Modifier and Type | Field and Description |
|---|---|
weka.classifiers.AbstractClassifier |
Model
Link to Weka-based model
|
boolean |
model_defined
Whether model type has been defined
|
protected java.lang.String[] |
Model_Options
Options supplied when instantiating Model
|
protected java.lang.String |
Model_Type
Name of model type currently in use
|
ClassNames, NClassesAttributeSelector, trained, TrainingStats, validated, ValidationStats| Constructor and Description |
|---|
WekaClassifier()
Create a WekaClassifier using a "rules.ZeroR" model
|
WekaClassifier(java.lang.String model_type,
java.lang.String[] options)
Create a Weka model with a specified model and options
|
| Modifier and Type | Method and Description |
|---|---|
WekaClassifier |
clone() |
java.util.List<org.apache.commons.lang3.tuple.Pair<java.lang.String,Citation>> |
getCitations()
Return a list of citations for this object and any underlying objects.
|
java.lang.String |
getModelFull()
Return model name and options
|
java.lang.String |
getModelName()
Return the model name
|
java.lang.String[] |
getModelOptions()
Return the model options
|
protected java.lang.String |
printModel_protected()
Internal method that handles printing the model as a string.
|
java.util.List<java.lang.String> |
printModelDescriptionDetails(boolean htmlFormat)
Print details of the model.
|
java.lang.String |
printUsage()
Print out required format for options.
|
void |
run_protected(Dataset TestData)
Run a model without checking if stuff is trained (use carefully)
|
void |
setModel(java.lang.String model_type,
java.lang.String[] options)
Set the underlying Weka-based model
|
void |
setOptions(java.util.List OptionsObj)
Set any options for this object.
|
java.lang.String |
toString() |
protected void |
train_protected(Dataset TrainingData)
Train a model without evaluating performance
|
getClassNames, getNClasses, run, trainabout, crossValidate, crossValidate, crossValidate, done, externallyValidate, getAttributeSelector, getFilter, getTrainTime, getValidationMethod, handleSetCommand, isTrained, isValidated, loadState, printCommand, printDescription, printModel, resetModel, runCommand, saveCommand, saveState, setAttributeSelector, setComponent, setFilter, trainpublic weka.classifiers.AbstractClassifier Model
public boolean model_defined
protected java.lang.String Model_Type
protected java.lang.String[] Model_Options
public WekaClassifier(java.lang.String model_type,
java.lang.String[] options)
throws java.lang.Exception
model_type - Model type (ie trees.J48)options - Options for the modeljava.lang.Exceptionpublic WekaClassifier()
throws java.lang.Exception
java.lang.Exceptionpublic void setOptions(java.util.List OptionsObj)
throws java.lang.Exception
OptionssetOptions in interface OptionsOptionsObj - Array of options as Objects - can be nulljava.lang.Exception - if problem with inputspublic java.lang.String printUsage()
OptionsprintUsage in interface Optionspublic WekaClassifier clone()
clone in class BaseClassifierpublic final void setModel(java.lang.String model_type,
java.lang.String[] options)
throws java.lang.Exception
WekaModelpublic java.lang.String getModelName()
WekaModelgetModelName in interface WekaModelpublic java.lang.String[] getModelOptions()
WekaModelgetModelOptions in interface WekaModelpublic java.lang.String getModelFull()
WekaModelgetModelFull in interface WekaModelpublic java.lang.String toString()
toString in class java.lang.Objectprotected void train_protected(Dataset TrainingData)
BaseModeltrain_protected in class BaseModelTrainingData - Training datapublic void run_protected(Dataset TestData)
BaseModelrun_protected in class BaseModelTestData - Training dataprotected java.lang.String printModel_protected()
BaseModelprintModel_protected in class BaseModelpublic java.util.List<java.lang.String> printModelDescriptionDetails(boolean htmlFormat)
BaseModelBaseModel.printDescription(boolean).
Implementation note: No not add indentation for details. That is handled
by BaseModel.printDescription(boolean). You should also call the super
operation to get the Normalizer and Attribute selector settings
printModelDescriptionDetails in class BaseModelhtmlFormat - Whether to use HTML formatpublic java.util.List<org.apache.commons.lang3.tuple.Pair<java.lang.String,Citation>> getCitations()
CitablegetCitations in interface CitablegetCitations in class BaseModel