Class Learner

Primary class for running model generators. It is designed to abstract the separation of training and test sets as well as best model selection.

Inheritance

System.Object

Learner

Inherited Members

System.Object.Equals(System.Object)

System.Object.Equals(System.Object, System.Object)

System.Object.GetHashCode()

System.Object.GetType()

System.Object.MemberwiseClone()

System.Object.ReferenceEquals(System.Object, System.Object)

System.Object.ToString()

Namespace:numl

Assembly:numl.dll

Syntax

public static class Learner

Methods

View Source

Best(IEnumerable<LearningModel>, ScoringMetric)

Retrieve best model (or model with the highest accuracy)

Declaration

public static LearningModel Best(this IEnumerable<LearningModel> models, ScoringMetric metric = ScoringMetric.Accuracy)

Parameters

Type	Name	Description
System.Collections.Generic.IEnumerable<LearningModel>	models	List of models.
ScoringMetric	metric	Scoring metric to use for model selection.

Returns

Type	Description
LearningModel	Best Model.

View Source

Learn(IEnumerable<Object>, Double, Int32, IGenerator)

Trains a single model based on a generator a predefined number of times with the provided examples and data split and selects the best (or most accurate) model.

Declaration

public static LearningModel Learn(IEnumerable<object> examples, double trainingPercentage, int repeat, IGenerator generator)

Parameters

Type	Name	Description
System.Collections.Generic.IEnumerable<System.Object>	examples	Source data.
System.Double	trainingPercentage	Data split percentage.
System.Int32	repeat	Number of repetitions per generator.
IGenerator	generator	Model generator used.

Returns

Type	Description
LearningModel	Best model for provided generator.

View Source

Learn(IEnumerable<Object>, Double, Int32, IGenerator[])

Trains an arbitrary number of models on the provided examples by creating a separation of data based on training percentage. Each generator is rerun a predetermined amount of times.

Declaration

public static LearningModel[] Learn(IEnumerable<object> examples, double trainingPercentage, int repeat, params IGenerator[] generators)

Parameters

Type	Name	Description
System.Collections.Generic.IEnumerable<System.Object>	examples	Source data.
System.Double	trainingPercentage	Data split percentage.
System.Int32	repeat	Number of repetitions per generator.
IGenerator[]	generators	Model generators used.

Returns

Type	Description
LearningModel[]	Best models for each generator.

Exceptions

Type	Condition
System.InvalidOperationException	Thrown when the requested operation is invalid.