org.encog.util.normalize
public class DataNormalization extends Object implements Serializable
Constructor and Description |
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DataNormalization() |
Modifier and Type | Method and Description |
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void |
addInputField(InputField f)
Add an input field.
|
void |
addOutputField(OutputField outputField)
Add an output field.
|
void |
addOutputField(OutputField outputField,
boolean ideal)
Add a field and allow it to be specified as an "ideal output field".
|
void |
addSegregator(Segregator segregator)
Add a segregator.
|
MLData |
buildForNetworkInput(double[] data)
Build "input data for a neural network" based on the input values
provided.
|
InputField |
findInputField(Class<?> clazz,
int count)
Find an input field by its class.
|
OutputField |
findOutputField(Class<?> clazz,
int count)
Find an output field by its class.
|
CSVFormat |
getCSVFormat() |
Set<OutputFieldGroup> |
getGroups() |
List<InputField> |
getInputFields() |
int |
getNetworkInputLayerSize() |
int |
getNetworkOutputLayerSize() |
int |
getOutputFieldCount() |
List<OutputField> |
getOutputFields() |
int |
getRecordCount() |
StatusReportable |
getReport() |
List<Segregator> |
getSegregators() |
NormalizationStorage |
getStorage() |
void |
init() |
void |
initForOutput()
Setup the row for output.
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void |
initForPass()
Setup the row for output.
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void |
process()
Call this method to begin the normalization process.
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void |
setCSVFormat(CSVFormat csvFormat)
Set the CSV format to use.
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void |
setReport(StatusReportable report)
Set the object that this one is reporting to.
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void |
setTarget(NormalizationStorage target)
Determines where the normalized data will be sent.
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boolean |
twoPassesNeeded() |
public void addInputField(InputField f)
f
- The input field to add.public void addOutputField(OutputField outputField)
outputField
- The output field to add.public void addOutputField(OutputField outputField, boolean ideal)
outputField
- The output field.ideal
- True if this is an ideal field.public void addSegregator(Segregator segregator)
segregator
- The segregator to add.public MLData buildForNetworkInput(double[] data)
data
- The input values to be normalized.public InputField findInputField(Class<?> clazz, int count)
clazz
- The input field class type you are looking for.count
- The instance of the input field needed, 0 for the first.public OutputField findOutputField(Class<?> clazz, int count)
clazz
- The output field class type you are looking for.count
- The instance of the output field needed, 0 for the first.public CSVFormat getCSVFormat()
public Set<OutputFieldGroup> getGroups()
public List<InputField> getInputFields()
public int getNetworkInputLayerSize()
public int getNetworkOutputLayerSize()
public int getOutputFieldCount()
public List<OutputField> getOutputFields()
public int getRecordCount()
public StatusReportable getReport()
public List<Segregator> getSegregators()
public NormalizationStorage getStorage()
public void initForOutput()
public void initForPass()
public void init()
public void process()
public void setCSVFormat(CSVFormat csvFormat)
csvFormat
- The CSV format to use.public void setReport(StatusReportable report)
report
- The object that progress reports should be sent to.public void setTarget(NormalizationStorage target)
target
- The target.public boolean twoPassesNeeded()
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