MLLIB::MlLinearModel Class Reference

Ridge regression / logistic regression built-in model. More...

#include <ml_linear_model.h>

Public Member Functions
	MlLinearModel (MlTaskType type=MlTaskType::Regression, double regularization=1.0)
MlTensor	predict (const MlTensor &input) const override
bool	save (const QString &path) const override
bool	load (const QString &path) override
QString	modelType () const override
MlTaskType	taskType () const override
const Eigen::MatrixXf &	weights () const
const Eigen::VectorXf &	bias () const
Public Member Functions inherited from MLLIB::MlModel
virtual	~MlModel ()=default

Additional Inherited Members
Public Types inherited from MLLIB::MlModel
typedef QSharedPointer< MlModel >	SPtr

Detailed Description

Ridge regression / logistic regression built-in model.

Definition at line 61 of file ml_linear_model.h.

Inheritance diagram for MLLIB::MlLinearModel:

Constructor & Destructor Documentation

MlLinearModel()

MlLinearModel::MlLinearModel	(	MlTaskType	type = MlTaskType::Regression,
		double	regularization = 1.0 )

Construct a linear model.

Parameters

[in]	type	Task type (Regression or Classification).
[in]	regularization	Ridge / L2 regularization strength (lambda).

Definition at line 75 of file ml_linear_model.cpp.

Member Function Documentation

bias()

const VectorXf & MlLinearModel::bias

(

)

const

Returns

Const reference to the bias vector (n_outputs).

Definition at line 222 of file ml_linear_model.cpp.

load()

bool MlLinearModel::load ( const QString & path )

overridevirtual

Load a model from disk.

Parameters

[in]

path

File path.

Returns

True if successful.

Implements MLLIB::MlModel.

Definition at line 151 of file ml_linear_model.cpp.

modelType()

QString MlLinearModel::modelType ( ) const

overridevirtual

Returns

Human-readable model type name.

Implements MLLIB::MlModel.

Definition at line 201 of file ml_linear_model.cpp.

predict()

MlTensor MlLinearModel::predict ( const MlTensor & input ) const

overridevirtual

Run inference on the given input tensor.

Parameters

[in]

input

The input data.

Returns

The prediction result.

Implements MLLIB::MlModel.

Definition at line 83 of file ml_linear_model.cpp.

save()

bool MlLinearModel::save ( const QString & path ) const

overridevirtual

Serialise the model to disk.

Parameters

[in]

path

File path.

Returns

True if successful.

Implements MLLIB::MlModel.

Definition at line 102 of file ml_linear_model.cpp.

taskType()

MlTaskType MlLinearModel::taskType ( ) const

overridevirtual

Returns

The task type this model is configured for.

Implements MLLIB::MlModel.

Definition at line 208 of file ml_linear_model.cpp.

weights()

const MatrixXf & MlLinearModel::weights

(

)

const

Returns

Const reference to the weight matrix (n_features x n_outputs).

Definition at line 215 of file ml_linear_model.cpp.

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The documentation for this class was generated from the following files:

• src/libraries/ml/ml_linear_model.h
• src/libraries/ml/ml_linear_model.cpp