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SG_ADD refactor #8

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Nov 22, 2018
Merged

SG_ADD refactor #8

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14 changes: 7 additions & 7 deletions shogun/classifier/FeatureBlockLogisticRegression.cpp
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Expand Up @@ -57,13 +57,13 @@ CFeatureBlockLogisticRegression::~CFeatureBlockLogisticRegression()

void CFeatureBlockLogisticRegression::register_parameters()
{
SG_ADD((CSGObject**)&m_feature_relation, "feature_relation", "feature relation", MS_NOT_AVAILABLE);
SG_ADD(&m_z, "z", "regularization coefficient", MS_AVAILABLE);
SG_ADD(&m_q, "q", "q of L1/Lq", MS_AVAILABLE);
SG_ADD(&m_termination, "termination", "termination", MS_NOT_AVAILABLE);
SG_ADD(&m_regularization, "regularization", "regularization", MS_NOT_AVAILABLE);
SG_ADD(&m_tolerance, "tolerance", "tolerance", MS_NOT_AVAILABLE);
SG_ADD(&m_max_iter, "max_iter", "maximum number of iterations", MS_NOT_AVAILABLE);
SG_ADD((CSGObject**)&m_feature_relation, "feature_relation", "feature relation");
SG_ADD(&m_z, "z", "regularization coefficient", ParameterProperties::HYPER);
SG_ADD(&m_q, "q", "q of L1/Lq", ParameterProperties::HYPER);
SG_ADD(&m_termination, "termination", "termination");
SG_ADD(&m_regularization, "regularization", "regularization");
SG_ADD(&m_tolerance, "tolerance", "tolerance");
SG_ADD(&m_max_iter, "max_iter", "maximum number of iterations");
}

CIndexBlockRelation* CFeatureBlockLogisticRegression::get_feature_relation() const
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8 changes: 4 additions & 4 deletions shogun/classifier/svm/SVMLin.cpp
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Expand Up @@ -43,12 +43,12 @@ CSVMLin::~CSVMLin()
void CSVMLin::init()
{
SG_ADD(
&use_bias, "use_bias", "Indicates if bias is used.", MS_NOT_AVAILABLE);
&use_bias, "use_bias", "Indicates if bias is used.");
SG_ADD(
&C1, "C1", "C constant for negatively labeled examples.", MS_AVAILABLE);
&C1, "C1", "C constant for negatively labeled examples.", ParameterProperties::HYPER);
SG_ADD(
&C2, "C2", "C constant for positively labeled examples.", MS_AVAILABLE);
SG_ADD(&epsilon, "epsilon", "Convergence precision.", MS_NOT_AVAILABLE);
&C2, "C2", "C constant for positively labeled examples.", ParameterProperties::HYPER);
SG_ADD(&epsilon, "epsilon", "Convergence precision.");
}

bool CSVMLin::train_machine(CFeatures* data)
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18 changes: 9 additions & 9 deletions shogun/classifier/svm/SVMSGD.cpp
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Expand Up @@ -213,16 +213,16 @@ void CSVMSGD::init()
loss=new CHingeLoss();
SG_REF(loss);

SG_ADD(&C1, "C1", "Cost constant 1.", MS_AVAILABLE);
SG_ADD(&C2, "C2", "Cost constant 2.", MS_AVAILABLE);
SG_ADD(&wscale, "wscale", "W scale", MS_NOT_AVAILABLE);
SG_ADD(&bscale, "bscale", "b scale", MS_NOT_AVAILABLE);
SG_ADD(&epochs, "epochs", "epochs", MS_NOT_AVAILABLE);
SG_ADD(&skip, "skip", "skip", MS_NOT_AVAILABLE);
SG_ADD(&count, "count", "count", MS_NOT_AVAILABLE);
SG_ADD(&C1, "C1", "Cost constant 1.", ParameterProperties::HYPER);
SG_ADD(&C2, "C2", "Cost constant 2.", ParameterProperties::HYPER);
SG_ADD(&wscale, "wscale", "W scale");
SG_ADD(&bscale, "bscale", "b scale");
SG_ADD(&epochs, "epochs", "epochs");
SG_ADD(&skip, "skip", "skip");
SG_ADD(&count, "count", "count");
SG_ADD(
&use_bias, "use_bias", "Indicates if bias is used.", MS_NOT_AVAILABLE);
&use_bias, "use_bias", "Indicates if bias is used.");
SG_ADD(
&use_regularized_bias, "use_regularized_bias",
"Indicates if bias is regularized.", MS_NOT_AVAILABLE);
"Indicates if bias is regularized.");
}
4 changes: 2 additions & 2 deletions shogun/kernel/string/DistantSegmentsKernel.cpp
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Expand Up @@ -43,8 +43,8 @@ bool CDistantSegmentsKernel::init(CFeatures* l, CFeatures* r)

void CDistantSegmentsKernel::init()
{
SG_ADD(&m_delta, "delta", "Delta parameter of the DS-Kernel", MS_AVAILABLE);
SG_ADD(&m_theta, "theta", "Theta parameter of the DS-Kernel", MS_AVAILABLE);
SG_ADD(&m_delta, "delta", "Delta parameter of the DS-Kernel", ParameterProperties::HYPER);
SG_ADD(&m_theta, "theta", "Theta parameter of the DS-Kernel", ParameterProperties::HYPER);
}

float64_t CDistantSegmentsKernel::compute(int32_t idx_a, int32_t idx_b)
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11 changes: 5 additions & 6 deletions shogun/mathematics/SparseInverseCovariance.cpp
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Expand Up @@ -31,12 +31,11 @@ CSparseInverseCovariance::~CSparseInverseCovariance()
void CSparseInverseCovariance::register_parameters()
{
SG_ADD(&m_lasso_max_iter,"lasso_max_iter",
"maximum iteration of LASSO step",MS_NOT_AVAILABLE);
SG_ADD(&m_max_iter,"max_iter","maximum total iteration",
MS_NOT_AVAILABLE);
SG_ADD(&m_f_gap,"f_gap","f gap",MS_NOT_AVAILABLE);
SG_ADD(&m_x_gap,"x_gap","x gap",MS_NOT_AVAILABLE);
SG_ADD(&m_xtol,"xtol","xtol",MS_NOT_AVAILABLE);
"maximum iteration of LASSO step");
SG_ADD(&m_max_iter,"max_iter","maximum total iteration");
SG_ADD(&m_f_gap,"f_gap","f gap");
SG_ADD(&m_x_gap,"x_gap","x gap");
SG_ADD(&m_xtol,"xtol","xtol");
}

SGMatrix<float64_t> CSparseInverseCovariance::estimate(SGMatrix<float64_t> S, float64_t lambda_c)
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6 changes: 3 additions & 3 deletions shogun/multiclass/MulticlassLogisticRegression.cpp
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Expand Up @@ -42,9 +42,9 @@ void CMulticlassLogisticRegression::init_defaults()

void CMulticlassLogisticRegression::register_parameters()
{
SG_ADD(&m_z, "m_z", "regularization constant",MS_AVAILABLE);
SG_ADD(&m_epsilon, "m_epsilon", "tolerance epsilon",MS_NOT_AVAILABLE);
SG_ADD(&m_max_iter, "m_max_iter", "max number of iterations",MS_NOT_AVAILABLE);
SG_ADD(&m_z, "m_z", "regularization constant", ParameterProperties::HYPER);
SG_ADD(&m_epsilon, "m_epsilon", "tolerance epsilon");
SG_ADD(&m_max_iter, "m_max_iter", "max number of iterations");
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we should introduce an attribute for parameters like this one .... these are hyper-parameters, but not in the classical sense (as in that we want to tune them). But still free parameters ...
@vigsterkr @lisitsyn ?

}

CMulticlassLogisticRegression::~CMulticlassLogisticRegression()
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6 changes: 3 additions & 3 deletions shogun/multiclass/MulticlassTreeGuidedLogisticRegression.cpp
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Expand Up @@ -41,9 +41,9 @@ void CMulticlassTreeGuidedLogisticRegression::init_defaults()

void CMulticlassTreeGuidedLogisticRegression::register_parameters()
{
SG_ADD(&m_z, "m_z", "regularization constant",MS_AVAILABLE);
SG_ADD(&m_epsilon, "m_epsilon", "tolerance epsilon",MS_NOT_AVAILABLE);
SG_ADD(&m_max_iter, "m_max_iter", "max number of iterations",MS_NOT_AVAILABLE);
SG_ADD(&m_z, "m_z", "regularization constant", ParameterProperties::HYPER);
SG_ADD(&m_epsilon, "m_epsilon", "tolerance epsilon");
SG_ADD(&m_max_iter, "m_max_iter", "max number of iterations");
}

CMulticlassTreeGuidedLogisticRegression::~CMulticlassTreeGuidedLogisticRegression()
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8 changes: 4 additions & 4 deletions shogun/optimization/NLOPTMinimizer.cpp
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Expand Up @@ -57,13 +57,13 @@ void CNLOPTMinimizer::init()
m_target_variable=SGVector<float64_t>();
set_nlopt_parameters();
SG_ADD(&m_max_iterations, "CNLOPTMinimizer__m_max_iterations",
"max_iterations in CNLOPTMinimizer", MS_NOT_AVAILABLE);
"max_iterations in CNLOPTMinimizer");
SG_ADD(&m_variable_tolerance, "CNLOPTMinimizer__m_variable_tolerance",
"variable_tolerance in CNLOPTMinimizer", MS_NOT_AVAILABLE);
"variable_tolerance in CNLOPTMinimizer");
SG_ADD(&m_function_tolerance, "CNLOPTMinimizer__m_function_tolerance",
"function_tolerance in CNLOPTMinimizer", MS_NOT_AVAILABLE);
"function_tolerance in CNLOPTMinimizer");
SG_ADD(&m_nlopt_algorithm_id, "CNLOPTMinimizer__m_nlopt_algorithm_id",
"nlopt_algorithm_id in CNLOPTMinimizer", MS_NOT_AVAILABLE);
"nlopt_algorithm_id in CNLOPTMinimizer");
#endif
}

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22 changes: 9 additions & 13 deletions shogun/structure/DualLibQPBMSOSVM.cpp
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Expand Up @@ -55,21 +55,17 @@ CDualLibQPBMSOSVM::~CDualLibQPBMSOSVM()

void CDualLibQPBMSOSVM::init()
{
SG_ADD(&m_TolRel, "m_TolRel", "Relative tolerance", MS_AVAILABLE);
SG_ADD(&m_TolAbs, "m_TolAbs", "Absolute tolerance", MS_AVAILABLE);
SG_ADD(&m_BufSize, "m_BuffSize", "Size of CP Buffer", MS_AVAILABLE);
SG_ADD(&m_lambda, "m_lambda", "Regularization constant lambda",
MS_AVAILABLE);
SG_ADD(&m_cleanICP, "m_cleanICP", "Inactive cutting plane removal flag",
MS_AVAILABLE);
SG_ADD(&m_TolRel, "m_TolRel", "Relative tolerance", ParameterProperties::HYPER);
SG_ADD(&m_TolAbs, "m_TolAbs", "Absolute tolerance", ParameterProperties::HYPER);
SG_ADD(&m_BufSize, "m_BuffSize", "Size of CP Buffer", ParameterProperties::HYPER);
SG_ADD(&m_lambda, "m_lambda", "Regularization constant lambda");
SG_ADD(&m_cleanICP, "m_cleanICP", "Inactive cutting plane removal flag");
SG_ADD(&m_cleanAfter,
"m_cleanAfter",
"Number of inactive iterations after which ICP will be removed",
MS_AVAILABLE);
SG_ADD(&m_K, "m_K", "Parameter K", MS_NOT_AVAILABLE);
SG_ADD(&m_Tmax, "m_Tmax", "Parameter Tmax", MS_AVAILABLE);
SG_ADD(&m_cp_models, "m_cp_models", "Number of cutting plane models",
MS_AVAILABLE);
"Number of inactive iterations after which ICP will be removed");
SG_ADD(&m_K, "m_K", "Parameter K");
SG_ADD(&m_Tmax, "m_Tmax", "Parameter Tmax", ParameterProperties::HYPER);
SG_ADD(&m_cp_models, "m_cp_models", "Number of cutting plane models");

set_TolRel(0.001);
set_TolAbs(0.0);
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4 changes: 2 additions & 2 deletions shogun/transfer/multitask/MultitaskL12LogisticRegression.cpp
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Expand Up @@ -49,8 +49,8 @@ CMultitaskL12LogisticRegression::CMultitaskL12LogisticRegression(

void CMultitaskL12LogisticRegression::init()
{
SG_ADD(&self->m_rho1,"rho1","rho L1/L2 regularization parameter",MS_AVAILABLE);
SG_ADD(&self->m_rho2,"rho2","rho L2 regularization parameter",MS_AVAILABLE);
SG_ADD(&self->m_rho1,"rho1","rho L1/L2 regularization parameter", ParameterProperties::HYPER);
SG_ADD(&self->m_rho2,"rho2","rho L2 regularization parameter", ParameterProperties::HYPER);
}

void CMultitaskL12LogisticRegression::set_rho1(float64_t rho1)
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12 changes: 6 additions & 6 deletions shogun/transfer/multitask/MultitaskLeastSquaresRegression.cpp
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Expand Up @@ -41,12 +41,12 @@ CMultitaskLeastSquaresRegression::~CMultitaskLeastSquaresRegression()

void CMultitaskLeastSquaresRegression::register_parameters()
{
SG_ADD(&m_z, "z", "regularization coefficient", MS_AVAILABLE);
SG_ADD(&m_q, "q", "q of L1/Lq", MS_AVAILABLE);
SG_ADD(&m_termination, "termination", "termination", MS_NOT_AVAILABLE);
SG_ADD(&m_regularization, "regularization", "regularization", MS_NOT_AVAILABLE);
SG_ADD(&m_tolerance, "tolerance", "tolerance", MS_NOT_AVAILABLE);
SG_ADD(&m_max_iter, "max_iter", "maximum number of iterations", MS_NOT_AVAILABLE);
SG_ADD(&m_z, "z", "regularization coefficient", ParameterProperties::HYPER);
SG_ADD(&m_q, "q", "q of L1/Lq", ParameterProperties::HYPER);
SG_ADD(&m_termination, "termination", "termination");
SG_ADD(&m_regularization, "regularization", "regularization");
SG_ADD(&m_tolerance, "tolerance", "tolerance");
SG_ADD(&m_max_iter, "max_iter", "maximum number of iterations");
}

void CMultitaskLeastSquaresRegression::initialize_parameters()
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2 changes: 1 addition & 1 deletion shogun/transfer/multitask/MultitaskLinearMachine.cpp
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Expand Up @@ -46,7 +46,7 @@ CMultitaskLinearMachine::~CMultitaskLinearMachine()

void CMultitaskLinearMachine::register_parameters()
{
SG_ADD((CSGObject**)&m_task_relation, "task_relation", "task relation", MS_NOT_AVAILABLE);
SG_ADD((CSGObject**)&m_task_relation, "task_relation", "task relation");
}

int32_t CMultitaskLinearMachine::get_current_task() const
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12 changes: 6 additions & 6 deletions shogun/transfer/multitask/MultitaskLogisticRegression.cpp
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Expand Up @@ -40,12 +40,12 @@ CMultitaskLogisticRegression::~CMultitaskLogisticRegression()

void CMultitaskLogisticRegression::register_parameters()
{
SG_ADD(&m_z, "z", "regularization coefficient", MS_AVAILABLE);
SG_ADD(&m_q, "q", "q of L1/Lq", MS_AVAILABLE);
SG_ADD(&m_termination, "termination", "termination", MS_NOT_AVAILABLE);
SG_ADD(&m_regularization, "regularization", "regularization", MS_NOT_AVAILABLE);
SG_ADD(&m_tolerance, "tolerance", "tolerance", MS_NOT_AVAILABLE);
SG_ADD(&m_max_iter, "max_iter", "maximum number of iterations", MS_NOT_AVAILABLE);
SG_ADD(&m_z, "z", "regularization coefficient", ParameterProperties::HYPER);
SG_ADD(&m_q, "q", "q of L1/Lq", ParameterProperties::HYPER);
SG_ADD(&m_termination, "termination", "termination");
SG_ADD(&m_regularization, "regularization", "regularization");
SG_ADD(&m_tolerance, "tolerance", "tolerance");
SG_ADD(&m_max_iter, "max_iter", "maximum number of iterations");
}

void CMultitaskLogisticRegression::initialize_parameters()
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2 changes: 1 addition & 1 deletion shogun/transfer/multitask/MultitaskTraceLogisticRegression.cpp
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Expand Up @@ -36,7 +36,7 @@ CMultitaskTraceLogisticRegression::CMultitaskTraceLogisticRegression(

void CMultitaskTraceLogisticRegression::init()
{
SG_ADD(&m_rho,"rho","rho",MS_AVAILABLE);
SG_ADD(&m_rho,"rho","rho", ParameterProperties::HYPER);
}

void CMultitaskTraceLogisticRegression::set_rho(float64_t rho)
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