AnalystWizard ClassEncog Machine Learning Framework for .Net
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.
Inheritance Hierarchy

System Object
  Encog.App.Analyst.Wizard AnalystWizard

Namespace: Encog.App.Analyst.Wizard
Assembly: encog-core-cs (in encog-core-cs.dll) Version: (

public class AnalystWizard

The AnalystWizard type exposes the following members.


Public methodAnalystWizard
Construct the analyst wizard.

Public methodEquals
Determines whether the specified Object is equal to the current Object.
(Inherited from Object.)
Protected methodFinalize
Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object.)
Public methodGetHashCode
Serves as a hash function for a particular type.
(Inherited from Object.)
Public methodGetType
Gets the type of the current instance.
(Inherited from Object.)
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodReanalyze
Reanalyze column ranges.
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
Public methodWizard(FileInfo, Boolean, AnalystFileFormat)
Analyze a file.
Public methodWizard(Uri, FileInfo, FileInfo, Boolean, AnalystFileFormat)
Analyze a file at the specified URL.
Public methodWizardRealTime

Public fieldStatic memberDefaultEvalPercent
The default evaluation percent.
Public fieldStatic memberDefaultTrainError
The default training error.
Public fieldStatic memberDefaultTrainPercent
The default training percent.
Public fieldStatic memberFileBalance
The balanced file.
Public fieldStatic memberFileCluster
The clustered file.
Public fieldStatic memberFileCode
The code file.
Public fieldStatic memberFileEval
The evaluation file.
Public fieldStatic memberFileEvalNorm
The eval file normalization file.
Public fieldStatic memberFileMl
The machine learning file.
Public fieldStatic memberFileNormalize
The normalized file.
Public fieldStatic memberFileOutput
The output file.
Public fieldStatic memberFilePre
The preprocess file.
Public fieldStatic memberFileRandom
The randomized file.
Public fieldStatic memberFileRaw
The raw file.
Public fieldStatic memberFileTrain
The training file.
Public fieldStatic memberFileTrainset
The training set.

Public propertyCodeEmbedData
Should code data be embedded.
Public propertyCodeTargetLanguage
The target language for code generation.
Public propertyEvidenceSegements
The number of evidence segments to use when mapping continuous values to Bayes.
Public propertyGoal
Set the goal.
Public propertyIncludeTargetField
Public propertyLagWindowSize
Public propertyLeadWindowSize
Public propertyMaxError
The maximum allowed training error.
Public propertyMethodType
Public propertyMissing
How should missing values be handled.
Public propertyNaiveBayes
Public propertyPreprocess
Should we preprocess.
Public propertyRange
Public propertyTargetField
Set the target field.
Public propertyTargetFieldName
The String name of the target field.
Public propertyTaskBalance
Public propertyTaskCluster
Public propertyTaskNormalize
Public propertyTaskRandomize
Public propertyTaskSegregate
See Also