Class QNTrainer

Namespace

NOpenNLP.Tools.Ml.Maxent.Quasinewton

Assembly

NOpenNLP.Tools.dll

Maxent model trainer using L-BFGS algorithm.

public class QNTrainer : AbstractEventTrainer, IEventTrainer

Inheritance

object

AbstractTrainer

AbstractEventTrainer

QNTrainer

Implements

IEventTrainer

Inherited Members

AbstractEventTrainer.DATA_INDEXER_PARAM

AbstractEventTrainer.DATA_INDEXER_ONE_PASS_VALUE

AbstractEventTrainer.DATA_INDEXER_TWO_PASS_VALUE

AbstractEventTrainer.DATA_INDEXER_ONE_PASS_REAL_VALUE

AbstractEventTrainer.GetDataIndexer(IObjectStream<Event>)

AbstractEventTrainer.Train(IDataIndexer)

AbstractEventTrainer.Train(IObjectStream<Event>)

AbstractTrainer.ALGORITHM_PARAM

AbstractTrainer.TRAINER_TYPE_PARAM

AbstractTrainer.CUTOFF_PARAM

AbstractTrainer.CUTOFF_DEFAULT

AbstractTrainer.ITERATIONS_PARAM

AbstractTrainer.ITERATIONS_DEFAULT

AbstractTrainer.VERBOSE_PARAM

AbstractTrainer.VERBOSE_DEFAULT

AbstractTrainer.trainingParameters

AbstractTrainer.reportMap

AbstractTrainer.printMessages

AbstractTrainer.Algorithm

AbstractTrainer.Cutoff

AbstractTrainer.Iterations

AbstractTrainer.AddToReport(string, string)

AbstractTrainer.Display(string)

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Constructors

QNTrainer()

public QNTrainer()

QNTrainer(TrainingParameters)

public QNTrainer(TrainingParameters parameters)

Parameters

parameters TrainingParameters

QNTrainer(bool)

public QNTrainer(bool printMessages)

Parameters

printMessages bool

QNTrainer(int)

public QNTrainer(int m)

Parameters

m int

QNTrainer(int, bool)

public QNTrainer(int m, bool verbose)

Parameters

m int

verbose bool

QNTrainer(int, int, bool)

public QNTrainer(int m, int maxFctEval, bool printMessages)

Parameters

m int

maxFctEval int

printMessages bool

Fields

L1COST_DEFAULT

public const double L1COST_DEFAULT = 0.1

Field Value

double

L1COST_PARAM

public const string L1COST_PARAM = "L1Cost"

Field Value

string

L2COST_DEFAULT

public const double L2COST_DEFAULT = 0.1

Field Value

double

L2COST_PARAM

public const string L2COST_PARAM = "L2Cost"

Field Value

string

MAXENT_QN_VALUE

public const string MAXENT_QN_VALUE = "MAXENT_QN"

Field Value

string

MAX_FCT_EVAL_DEFAULT

public const int MAX_FCT_EVAL_DEFAULT = 30000

Field Value

int

MAX_FCT_EVAL_PARAM

public const string MAX_FCT_EVAL_PARAM = "MaxFctEval"

Field Value

string

M_DEFAULT

public const int M_DEFAULT = 15

Field Value

int

M_PARAM

public const string M_PARAM = "NumOfUpdates"

Field Value

string

THREADS_DEFAULT

public const int THREADS_DEFAULT = 1

Field Value

int

THREADS_PARAM

public const string THREADS_PARAM = "Threads"

Field Value

string

Properties

IsSortAndMerge

Whether the data indexer should sort and merge the indexed events.

public override bool IsSortAndMerge { get; }

Property Value

bool

Methods

DoTrain(IDataIndexer)

Trains a model from the given, already indexed, training data.

public override IMaxentModel DoTrain(IDataIndexer indexer)

Parameters

indexer IDataIndexer

Returns

IMaxentModel

Init(TrainingParameters, IDictionary<string, string>?)

Initializes this trainer with the given parameters and report map.

public override void Init(TrainingParameters trainingParameters, IDictionary<string, string>? reportMap)

Parameters

trainingParameters TrainingParameters

reportMap IDictionary<string, string>

TrainModel(int, IDataIndexer)

public QNModel TrainModel(int iterations, IDataIndexer indexer)

Parameters

iterations int

indexer IDataIndexer

Returns

QNModel

Validate()

Checks the parameters. If a subclass overrides this, it should call the base implementation.

public override void Validate()

Exceptions

ArgumentException

Thrown if a parameter is not valid.