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, DiscreteClass, NClasses
AttributeSelector, trained, TrainingStats, validated, ValidationStats
Constructor and Description |
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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
|
classIsDiscrete, getClassCutoff, getClassNames, getNClasses, run, setClassContinuous, setClassCutoff, setClassDiscrete, train
about, crossValidate, externallyValidate, getAttributeSelector, getFilter, getTrainTime, getValidationMethod, handleSetCommand, isTrained, isValidated, loadState, printCommand, printDescription, printModel, resetModel, runCommand, saveCommand, saveState, setAttributeSelector, setComponent, setFilter, train
public 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.Exception
public WekaClassifier() throws java.lang.Exception
java.lang.Exception
public void setOptions(java.util.List OptionsObj) throws java.lang.Exception
Options
setOptions
in interface Options
OptionsObj
- Array of options as Objects - can be null
java.lang.Exception
- if problem with inputspublic java.lang.String printUsage()
Options
printUsage
in interface Options
public WekaClassifier clone()
clone
in class BaseClassifier
public final void setModel(java.lang.String model_type, java.lang.String[] options) throws java.lang.Exception
WekaModel
public java.lang.String getModelName()
WekaModel
getModelName
in interface WekaModel
public java.lang.String[] getModelOptions()
WekaModel
getModelOptions
in interface WekaModel
public java.lang.String getModelFull()
WekaModel
getModelFull
in interface WekaModel
public java.lang.String toString()
toString
in class java.lang.Object
protected void train_protected(Dataset TrainingData)
BaseModel
train_protected
in class BaseModel
TrainingData
- Training datapublic void run_protected(Dataset TestData)
BaseModel
run_protected
in class BaseModel
TestData
- Training dataprotected java.lang.String printModel_protected()
BaseModel
printModel_protected
in class BaseModel
public java.util.List<java.lang.String> printModelDescriptionDetails(boolean htmlFormat)
BaseModel
BaseModel.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 BaseModel
htmlFormat
- Whether to use HTML formatpublic java.util.List<org.apache.commons.lang3.tuple.Pair<java.lang.String,Citation>> getCitations()
Citable
getCitations
in interface Citable
getCitations
in class BaseModel