joshua.pro.Optimizer Class Reference

Collaboration diagram for joshua.pro.Optimizer:

List of all members.

Public Member Functions
	Optimizer (long _seed, int _sentNum, Vector< String > _output, double[] _initialTotalLambda, HashMap< String, String >[] _feat_hash, HashMap< String, String >[] _stats_hash, double _finalScore, EvaluationMetric _evalMetric, int _Tau, int _Xi, double _metricDiff, double[] _normalizationOptions, String _classifierAlg, String[] _classifierParam, String _trainMode, int _numSparseParam, int _numRegParam, String _nbestFormat)
double[]	run_Optimizer ()
double	computeCorpusMetricScore (double[] finalLambda)
Vector< String >	process_Params ()
Private Member Functions
Vector< String >	Sampler (int sentId)
double	Alpha (double x)
HashMap< String, Double >	compute_Score (int sentId, String[] cands)
void	normalizeLambda (double[] origLambda)
double	L_norm (double[] A, double pow)
void	normalizeLambda_mode3 (double[] origLambda)
Private Attributes
EvaluationMetric	evalMetric
Vector< String >	output
double[]	initialLambda
double[]	finalLambda
double[]	copyLambda
double	finalScore
double[]	normalizationOptions
HashMap< String, String >[]	feat_hash
HashMap< String, String >[]	stats_hash
Random	randgen
int	paramDim
int	regParamDim
int	sentNum
String	trainMode
int	Tau
int	Xi
double	metricDiff
String	classifierAlg
String	nbestFormat
String[]	classifierParam
Static Private Attributes
static final double	NegInf = (-1.0 / 0.0)
static final double	PosInf = (+1.0 / 0.0)

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Constructor & Destructor Documentation

joshua.pro.Optimizer.Optimizer	(	long	_seed,
		int	_sentNum,
		Vector< String >	_output,
		double[]	_initialTotalLambda,
		HashMap< String, String >[]	_feat_hash,
		HashMap< String, String >[]	_stats_hash,
		double	_finalScore,
		EvaluationMetric	_evalMetric,
		int	_Tau,
		int	_Xi,
		double	_metricDiff,
		double[]	_normalizationOptions,
		String	_classifierAlg,
		String[]	_classifierParam,
		String	_trainMode,
		int	_numSparseParam,
		int	_numRegParam,
		String	_nbestFormat
	)

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Member Function Documentation

double joshua.pro.Optimizer.Alpha

(

double

x

)

[private]

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HashMap<String, Double> joshua.pro.Optimizer.compute_Score	(	int	sentId,
		String[]	cands
	)		[private]

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double joshua.pro.Optimizer.computeCorpusMetricScore

(

double[]

finalLambda

)

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double joshua.pro.Optimizer.L_norm	(	double[]	A,
		double	pow
	)		[private]

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void joshua.pro.Optimizer.normalizeLambda

(

double[]

origLambda

)

[private]

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void joshua.pro.Optimizer.normalizeLambda_mode3

(

double[]

origLambda

)

[private]

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Vector<String> joshua.pro.Optimizer.process_Params

(

)

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double [] joshua.pro.Optimizer.run_Optimizer

(

)

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Vector<String> joshua.pro.Optimizer.Sampler

(

int

sentId

)

[private]

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Member Data Documentation

String joshua.pro.Optimizer.classifierAlg [private]

String [] joshua.pro.Optimizer.classifierParam [private]

double [] joshua.pro.Optimizer.copyLambda [private]

EvaluationMetric joshua.pro.Optimizer.evalMetric [private]

HashMap<String, String> [] joshua.pro.Optimizer.feat_hash [private]

double [] joshua.pro.Optimizer.finalLambda [private]

double joshua.pro.Optimizer.finalScore [private]

double [] joshua.pro.Optimizer.initialLambda [private]

double joshua.pro.Optimizer.metricDiff [private]

String joshua.pro.Optimizer.nbestFormat [private]

final double joshua.pro.Optimizer.NegInf = (-1.0 / 0.0) [static, private]

double [] joshua.pro.Optimizer.normalizationOptions [private]

Vector<String> joshua.pro.Optimizer.output [private]

int joshua.pro.Optimizer.paramDim [private]

final double joshua.pro.Optimizer.PosInf = (+1.0 / 0.0) [static, private]

Random joshua.pro.Optimizer.randgen [private]

int joshua.pro.Optimizer.regParamDim [private]

int joshua.pro.Optimizer.sentNum [private]

HashMap<String, String> [] joshua.pro.Optimizer.stats_hash [private]

int joshua.pro.Optimizer.Tau [private]

String joshua.pro.Optimizer.trainMode [private]

int joshua.pro.Optimizer.Xi [private]