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java.lang.Objectorg.encog.app.analyst.wizard.AnalystWizard
public class AnalystWizard
The Encog Analyst Wizard can be used to create Encog Analyst script files from a CSV file. This class is typically used by the Encog Workbench, but it can easily be used from any program to create a starting point for an Encog Analyst Script. Several items must be provided to the wizard. Desired Machine Learning Method: This is the machine learning method that you would like the wizard to use. This might be a neural network, SVM or other supported method. Normalization Range: This is the range that the data should be normalized into. Some machine learning methods perform better with different ranges. The two ranges supported by the wizard are -1 to 1 and 0 to 1. Goal: What are we trying to accomplish. Is this a classification, regression or autoassociation problem.
Field Summary | |
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static int |
DEFAULT_EVAL_PERCENT
The default evaluation percent. |
static double |
DEFAULT_TRAIN_ERROR
The default training error. |
static int |
DEFAULT_TRAIN_PERCENT
The default training percent. |
static String |
FILE_BALANCE
The balanced file. |
static String |
FILE_CLUSTER
The clustered file. |
static String |
FILE_CODE
The generated code file. |
static String |
FILE_EVAL
The evaluation file. |
static String |
FILE_EVAL_NORM
The eval file normalization file. |
static String |
FILE_ML
The machine learning file. |
static String |
FILE_NORMALIZE
The normalized file. |
static String |
FILE_OUTPUT
The output file. |
static String |
FILE_PRE
The processed data. |
static String |
FILE_RANDOM
The randomized file. |
static String |
FILE_RAW
The raw file. |
static String |
FILE_TRAIN
The training file. |
static String |
FILE_TRAINSET
The training set. |
Constructor Summary | |
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AnalystWizard(EncogAnalyst theAnalyst)
Construct the analyst wizard. |
Method Summary | |
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TargetLanguage |
getCodeTargetLanguage()
|
int |
getEvidenceSegements()
|
AnalystGoal |
getGoal()
|
int |
getLagWindowSize()
|
int |
getLeadWindowSize()
|
double |
getMaxError()
|
WizardMethodType |
getMethodType()
|
HandleMissingValues |
getMissing()
|
NormalizeRange |
getRange()
|
AnalystField |
getTargetField()
|
boolean |
isCodeEmbedData()
|
boolean |
isIncludeTargetField()
|
boolean |
isNaiveBayes()
|
boolean |
isPreprocess()
|
boolean |
isTaskBalance()
|
boolean |
isTaskCluster()
|
boolean |
isTaskNormalize()
|
boolean |
isTaskRandomize()
|
boolean |
isTaskSegregate()
|
void |
reanalyze()
Reanalyze column ranges. |
void |
setCodeEmbedData(boolean codeEmbedData)
|
void |
setCodeTargetLanguage(TargetLanguage codeTargetLanguage)
|
void |
setEvidenceSegements(int evidenceSegements)
|
void |
setGoal(AnalystGoal theGoal)
Set the goal. |
void |
setIncludeTargetField(boolean theIncludeTargetField)
|
void |
setLagWindowSize(int theLagWindowSize)
|
void |
setLeadWindowSize(int theLeadWindowSize)
|
void |
setMaxError(double maxError)
|
void |
setMethodType(WizardMethodType theMethodType)
|
void |
setMissing(HandleMissingValues missing)
|
void |
setNaiveBayes(boolean naiveBayes)
|
void |
setPreprocess(boolean preprocess)
|
void |
setRange(NormalizeRange theRange)
|
void |
setTargetField(AnalystField theTargetField)
Set the target field. |
void |
setTargetField(String theTargetField)
|
void |
setTaskBalance(boolean theTaskBalance)
|
void |
setTaskCluster(boolean theTaskCluster)
|
void |
setTaskNormalize(boolean theTaskNormalize)
|
void |
setTaskRandomize(boolean theTaskRandomize)
|
void |
setTaskSegregate(boolean theTaskSegregate)
|
void |
wizard(File analyzeFile,
boolean b,
AnalystFileFormat format)
Analyze a file. |
void |
wizard(URL url,
File saveFile,
File analyzeFile,
boolean b,
AnalystFileFormat format)
Analyze a file at the specified URL. |
void |
wizardRealTime(List<SourceElement> sourceData,
File csvFile,
int backwardWindow,
int forwardWindow,
PredictionType prediction,
String predictField)
|
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Field Detail |
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public static final int DEFAULT_TRAIN_PERCENT
public static final int DEFAULT_EVAL_PERCENT
public static final double DEFAULT_TRAIN_ERROR
public static final String FILE_PRE
public static final String FILE_RAW
public static final String FILE_NORMALIZE
public static final String FILE_RANDOM
public static final String FILE_TRAIN
public static final String FILE_EVAL
public static final String FILE_EVAL_NORM
public static final String FILE_TRAINSET
public static final String FILE_ML
public static final String FILE_OUTPUT
public static final String FILE_BALANCE
public static final String FILE_CLUSTER
public static final String FILE_CODE
Constructor Detail |
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public AnalystWizard(EncogAnalyst theAnalyst)
theAnalyst
- The analyst to use.Method Detail |
---|
public AnalystGoal getGoal()
public int getLagWindowSize()
public int getLeadWindowSize()
public WizardMethodType getMethodType()
public NormalizeRange getRange()
public AnalystField getTargetField()
public boolean isIncludeTargetField()
public boolean isTaskBalance()
public boolean isTaskCluster()
public boolean isTaskNormalize()
public boolean isTaskRandomize()
public boolean isTaskSegregate()
public void reanalyze()
public void setGoal(AnalystGoal theGoal)
theGoal
- The goal.public void setIncludeTargetField(boolean theIncludeTargetField)
theIncludeTargetField
- the includeTargetField to setpublic void setLagWindowSize(int theLagWindowSize)
theLagWindowSize
- the lagWindowSize to setpublic void setLeadWindowSize(int theLeadWindowSize)
theLeadWindowSize
- the leadWindowSize to setpublic void setMethodType(WizardMethodType theMethodType)
theMethodType
- the methodType to setpublic void setRange(NormalizeRange theRange)
theRange
- the range to setpublic void setTargetField(AnalystField theTargetField)
theTargetField
- The target field.public void setTaskBalance(boolean theTaskBalance)
theTaskBalance
- the taskBalance to setpublic void setTaskCluster(boolean theTaskCluster)
theTaskCluster
- the taskCluster to setpublic void setTaskNormalize(boolean theTaskNormalize)
theTaskNormalize
- the taskNormalize to setpublic void setTaskRandomize(boolean theTaskRandomize)
theTaskRandomize
- the taskRandomize to setpublic void setTaskSegregate(boolean theTaskSegregate)
theTaskSegregate
- the taskSegregate to setpublic void wizardRealTime(List<SourceElement> sourceData, File csvFile, int backwardWindow, int forwardWindow, PredictionType prediction, String predictField)
public void wizard(File analyzeFile, boolean b, AnalystFileFormat format)
analyzeFile
- The file to analyze.b
- True if there are headers.format
- The file format.public void wizard(URL url, File saveFile, File analyzeFile, boolean b, AnalystFileFormat format)
url
- The URL to analyze.saveFile
- The save file.analyzeFile
- The Encog analyst file.b
- True if there are headers.format
- The file format.public HandleMissingValues getMissing()
public void setMissing(HandleMissingValues missing)
missing
- the missing to setpublic boolean isNaiveBayes()
public void setNaiveBayes(boolean naiveBayes)
naiveBayes
- the naiveBayes to setpublic int getEvidenceSegements()
public void setEvidenceSegements(int evidenceSegements)
evidenceSegements
- the evidenceSegements to setpublic double getMaxError()
public void setMaxError(double maxError)
public void setTargetField(String theTargetField)
public TargetLanguage getCodeTargetLanguage()
public void setCodeTargetLanguage(TargetLanguage codeTargetLanguage)
codeTargetLanguage
- the codeTargetLanguage to setpublic boolean isCodeEmbedData()
public void setCodeEmbedData(boolean codeEmbedData)
codeEmbedData
- the codeEmbedData to setpublic boolean isPreprocess()
public void setPreprocess(boolean preprocess)
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