org.encog.app.analyst.wizard

Class AnalystWizard

java.lang.Object

org.encog.app.analyst.wizard.AnalystWizard

public class AnalystWizard
extends java.lang.Object

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

Fields

Modifier and Type	Field and Description
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 java.lang.String	FILE_BALANCE The balanced file.
static java.lang.String	FILE_CLUSTER The clustered file.
static java.lang.String	FILE_CODE The generated code file.
static java.lang.String	FILE_EVAL The evaluation file.
static java.lang.String	FILE_EVAL_NORM The eval file normalization file.
static java.lang.String	FILE_ML The machine learning file.
static java.lang.String	FILE_NORMALIZE The normalized file.
static java.lang.String	FILE_OUTPUT The output file.
static java.lang.String	FILE_PRE The processed data.
static java.lang.String	FILE_RANDOM The randomized file.
static java.lang.String	FILE_RAW The raw file.
static java.lang.String	FILE_TRAIN The training file.
static java.lang.String	FILE_TRAINSET The training set.

Constructor Summary

Constructors

Constructor and Description
AnalystWizard(EncogAnalyst theAnalyst) Construct the analyst wizard.

Method Summary

Modifier and Type	Method and Description
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(java.lang.String theTargetField)
void	setTaskBalance(boolean theTaskBalance)
void	setTaskCluster(boolean theTaskCluster)
void	setTaskNormalize(boolean theTaskNormalize)
void	setTaskRandomize(boolean theTaskRandomize)
void	setTaskSegregate(boolean theTaskSegregate)
void	wizard(java.io.File analyzeFile, boolean b, AnalystFileFormat format) Analyze a file.
void	wizard(java.net.URL url, java.io.File saveFile, java.io.File analyzeFile, boolean b, AnalystFileFormat format) Analyze a file at the specified URL.
void	wizardRealTime(java.util.List<SourceElement> sourceData, java.io.File csvFile, int backwardWindow, int forwardWindow, PredictionType prediction, java.lang.String predictField)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

DEFAULT_TRAIN_PERCENT

public static final int DEFAULT_TRAIN_PERCENT

The default training percent.

See Also:

Constant Field Values

DEFAULT_EVAL_PERCENT

public static final int DEFAULT_EVAL_PERCENT

The default evaluation percent.

See Also:

Constant Field Values

DEFAULT_TRAIN_ERROR

public static final double DEFAULT_TRAIN_ERROR

The default training error.

See Also:

Constant Field Values

FILE_PRE

public static final java.lang.String FILE_PRE

The processed data.

See Also:

Constant Field Values

FILE_RAW

public static final java.lang.String FILE_RAW

The raw file.

See Also:

Constant Field Values

FILE_NORMALIZE

public static final java.lang.String FILE_NORMALIZE

The normalized file.

See Also:

Constant Field Values

FILE_RANDOM

public static final java.lang.String FILE_RANDOM

The randomized file.

See Also:

Constant Field Values

FILE_TRAIN

public static final java.lang.String FILE_TRAIN

The training file.

See Also:

Constant Field Values

FILE_EVAL

public static final java.lang.String FILE_EVAL

The evaluation file.

See Also:

Constant Field Values

FILE_EVAL_NORM

public static final java.lang.String FILE_EVAL_NORM

The eval file normalization file.

See Also:

Constant Field Values

FILE_TRAINSET

public static final java.lang.String FILE_TRAINSET

The training set.

See Also:

Constant Field Values

FILE_ML

public static final java.lang.String FILE_ML

The machine learning file.

See Also:

Constant Field Values

FILE_OUTPUT

public static final java.lang.String FILE_OUTPUT

The output file.

See Also:

Constant Field Values

FILE_BALANCE

public static final java.lang.String FILE_BALANCE

The balanced file.

See Also:

Constant Field Values

FILE_CLUSTER

public static final java.lang.String FILE_CLUSTER

The clustered file.

See Also:

Constant Field Values

FILE_CODE

public static final java.lang.String FILE_CODE

The generated code file.

See Also:

Constant Field Values

Constructor Detail

AnalystWizard

public AnalystWizard(EncogAnalyst theAnalyst)

Construct the analyst wizard.

Parameters:

theAnalyst - The analyst to use.

Method Detail

getGoal

public AnalystGoal getGoal()

Returns:

The analyst goal.

getLagWindowSize

public int getLagWindowSize()

Returns:

the lagWindowSize

getLeadWindowSize

public int getLeadWindowSize()

Returns:

the leadWindowSize

getMethodType

public WizardMethodType getMethodType()

Returns:

the methodType

getRange

public NormalizeRange getRange()

Returns:

the range

getTargetField

public AnalystField getTargetField()

Returns:

Get the target field.

isIncludeTargetField

public boolean isIncludeTargetField()

Returns:

the includeTargetField

isTaskBalance

public boolean isTaskBalance()

Returns:

the taskBalance

isTaskCluster

public boolean isTaskCluster()

Returns:

the taskCluster

isTaskNormalize

public boolean isTaskNormalize()

Returns:

the taskNormalize

isTaskRandomize

public boolean isTaskRandomize()

Returns:

the taskRandomize

isTaskSegregate

public boolean isTaskSegregate()

Returns:

the taskSegregate

reanalyze

public void reanalyze()

Reanalyze column ranges.

setGoal

public void setGoal(AnalystGoal theGoal)

Set the goal.

Parameters:

theGoal - The goal.

setIncludeTargetField

public void setIncludeTargetField(boolean theIncludeTargetField)

Parameters:

theIncludeTargetField - the includeTargetField to set

setLagWindowSize

public void setLagWindowSize(int theLagWindowSize)

Parameters:

theLagWindowSize - the lagWindowSize to set

setLeadWindowSize

public void setLeadWindowSize(int theLeadWindowSize)

Parameters:

theLeadWindowSize - the leadWindowSize to set

setMethodType

public void setMethodType(WizardMethodType theMethodType)

Parameters:

theMethodType - the methodType to set

setRange

public void setRange(NormalizeRange theRange)

Parameters:

theRange - the range to set

setTargetField

public void setTargetField(AnalystField theTargetField)

Set the target field.

Parameters:

theTargetField - The target field.

setTaskBalance

public void setTaskBalance(boolean theTaskBalance)

Parameters:

theTaskBalance - the taskBalance to set

setTaskCluster

public void setTaskCluster(boolean theTaskCluster)

Parameters:

theTaskCluster - the taskCluster to set

setTaskNormalize

public void setTaskNormalize(boolean theTaskNormalize)

Parameters:

theTaskNormalize - the taskNormalize to set

setTaskRandomize

public void setTaskRandomize(boolean theTaskRandomize)

Parameters:

theTaskRandomize - the taskRandomize to set

setTaskSegregate

public void setTaskSegregate(boolean theTaskSegregate)

Parameters:

theTaskSegregate - the taskSegregate to set

wizardRealTime

public void wizardRealTime(java.util.List<SourceElement> sourceData,
                           java.io.File csvFile,
                           int backwardWindow,
                           int forwardWindow,
                           PredictionType prediction,
                           java.lang.String predictField)

wizard

public void wizard(java.io.File analyzeFile,
                   boolean b,
                   AnalystFileFormat format)

Analyze a file.

Parameters:

analyzeFile - The file to analyze.

b - True if there are headers.

format - The file format.

wizard

public void wizard(java.net.URL url,
                   java.io.File saveFile,
                   java.io.File analyzeFile,
                   boolean b,
                   AnalystFileFormat format)

Analyze a file at the specified URL.

Parameters:

url - The URL to analyze.

saveFile - The save file.

analyzeFile - The Encog analyst file.

b - True if there are headers.

format - The file format.

getMissing

public HandleMissingValues getMissing()

Returns:

the missing

setMissing

public void setMissing(HandleMissingValues missing)

Parameters:

missing - the missing to set

isNaiveBayes

public boolean isNaiveBayes()

Returns:

the naiveBayes

setNaiveBayes

public void setNaiveBayes(boolean naiveBayes)

Parameters:

naiveBayes - the naiveBayes to set

getEvidenceSegements

public int getEvidenceSegements()

Returns:

the evidenceSegements

setEvidenceSegements

public void setEvidenceSegements(int evidenceSegements)

Parameters:

evidenceSegements - the evidenceSegements to set

getMaxError

public double getMaxError()

setMaxError

public void setMaxError(double maxError)

setTargetField

public void setTargetField(java.lang.String theTargetField)

getCodeTargetLanguage

public TargetLanguage getCodeTargetLanguage()

Returns:

the codeTargetLanguage

setCodeTargetLanguage

public void setCodeTargetLanguage(TargetLanguage codeTargetLanguage)

Parameters:

codeTargetLanguage - the codeTargetLanguage to set

isCodeEmbedData

public boolean isCodeEmbedData()

Returns:

the codeEmbedData

setCodeEmbedData

public void setCodeEmbedData(boolean codeEmbedData)

Parameters:

codeEmbedData - the codeEmbedData to set

isPreprocess

public boolean isPreprocess()

setPreprocess

public void setPreprocess(boolean preprocess)