SG++
python.learner.Regressor.Regressor Class Reference

Subclass of Learner, responsible for regression. More...

Inheritance diagram for python.learner.Regressor.Regressor:

Public Member Functions

def __init__ (self)
 constructor More...
 
def evalError (self, data, alpha)
 Evaluate regression MSE. More...
 
def getL2NormError (self)
 calculate L2-norm of error More...
 
def getMaxError (self)
 calculate max error More...
 
def getMinError (self)
 calculate min error More...
 
def refineGrid (self)
 Refines grid with the number of points as specified in corresponding TrainingSpecification object. More...
 
def updateResults (self, alpha, trainSubset, testSubset=None)
 Update different statistics about training progress. More...
 

Static Public Attributes

 error = None
 Error vector. More...
 
 errors = None
 Errors per basis function. More...
 

Detailed Description

Subclass of Learner, responsible for regression.

The methods specific for regression are implemented here.

Constructor & Destructor Documentation

def python.learner.Regressor.Regressor.__init__ (   self)

constructor

Member Function Documentation

def python.learner.Regressor.Regressor.evalError (   self,
  data,
  alpha 
)

Evaluate regression MSE.

Parameters
dataDataContainer dataset
alphaDataVector alpha-vector
Returns
: mean square error

References python.learner.Regressor.Regressor.error, and python.learner.Regressor.Regressor.errors.

Referenced by python.learner.Regressor.Regressor.updateResults(), python.uq.learner.Interpolant.Interpolant.updateResults(), and python.uq.learner.Regressor.Regressor.updateResults().

def python.learner.Regressor.Regressor.getL2NormError (   self)

calculate L2-norm of error

Returns
: last L2-norm of error
def python.learner.Regressor.Regressor.getMaxError (   self)

calculate max error

Returns
: max error
def python.learner.Regressor.Regressor.getMinError (   self)

calculate min error

Returns
: min error

Member Data Documentation

python.learner.Regressor.Regressor.error = None
static

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