string Solver.type BMRM
int BMRM.verbosity 2
int BMRM.maxNumOfIter 1000

// uncomment one of the following
double BMRM.relEpsilonTol .1
//double BMRM.epsilonTol 1e-5
//double BMRM.relGammaTol 1e-1
//double BMRM.gammaTol 1e-5

double BMRM.lambda .001
int InnerSolver.verbosity 0

// uncomment one of the following 3 inner solvers for L2 norm regularization
string BMRM.innerSolverType L2N2_DaiFletcherPGM
//string BMRM.innerSolverType L2N2_prLOQO
//string BMRM.innerSolverType L2N2_LineSearch

// uncomment the following if either L2N2_DaiFletcherPGM or L2N2_prLOQO is chosen
int L2N2_BMRMDualInnerSolver.maxGradSetSize 1000
int L2N2_BMRMDualInnerSolver.gradIdleAge 100
bool L2N2_BMRMDualInnerSolver.removeAllIdleGradients false

string Model.modelFile model.binary.l2.txt

// uncomment one of the following
string Loss.lossFunctionType HINGE
//string Loss.lossFunctionType SQUARED_HINGE
//string Loss.lossFunctionType LOGISTIC
//string Loss.lossFunctionType F_BETA
//string Loss.lossFunctionType ROC_SCORE
//string Loss.lossFunctionType EXPONENTIAL

//string Loss.lossFunctionType HUBER_HINGE
//double HUBER_HINGE.H 0.01

//string Loss.lossFunctionType NOVELTY_DETECTION
//double NOVELTY_DETECTION.rho 0.9


int Loss.verbosity 0
bool Loss.nonNegative true
int Data.verbosity 1
bool Data.bias false
string Data.format VECTOR_LABEL_VECTOR_FEATURE

// replace the following values by actual paths to feature vectors and labels files
string Data.featureFile training_bmrm
string Data.labelFile training_labels_bmrm