kusanagi.ghost.regression.GPRegressor.SPGP Class Reference

Inheritance diagram for kusanagi.ghost.regression.GPRegressor.SPGP:

Collaboration diagram for kusanagi.ghost.regression.GPRegressor.SPGP:

Public Member Functions
def	__init__
def	init_pseudo_inputs
def	set_dataset
def	init_log_likelihood
def	predict_symbolic
def	set_X_sp
def	get_params
def	loss_sp
def	train
def	set_state
def	get_state
Public Member Functions inherited from kusanagi.ghost.regression.GPRegressor.GP
def	__init__
def	set_dataset
def	append_dataset
def	init_loghyp
def	set_loghyp
def	get_params
def	set_params
def	init_log_likelihood
def	init_predict
def	predict_symbolic
def	predict
def	loss
def	train
def	load
def	save
def	set_state
def	get_state

Public Attributes
	X_sp_
	X_sp
	nlml_sp
	dnlml_sp
	beta_sp
	Lmm
	Amm
	should_recompile
	n_basis
Public Attributes inherited from kusanagi.ghost.regression.GPRegressor.GP
	profile
	compile_mode
	min_method
	state_changed
	should_recompile
	uncertain_inputs
	hyperparameter_gradients
	snr_penalty
	D
	E
	X_
	Y_
	loghyp_
	loghyp
	X
	Y
	K
	L
	beta
	nlml
	predict_
	predict_d_
	name
	filename
	ready
	N
	kernel_func
	dnlml

Constructor & Destructor Documentation

def kusanagi.ghost.regression.GPRegressor.SPGP.__init__	(		self,
			X_dataset,
			Y_dataset,
			name = 'SPGP',
			profile = False,
			n_basis = 100,
			uncertain_inputs = False,
			hyperparameter_gradients = False
	)

Member Function Documentation

def kusanagi.ghost.regression.GPRegressor.SPGP.get_params	(		self,
			symbolic = True
	)

def kusanagi.ghost.regression.GPRegressor.SPGP.get_state

(

self

)

def kusanagi.ghost.regression.GPRegressor.SPGP.init_log_likelihood

(

self

)

def kusanagi.ghost.regression.GPRegressor.SPGP.init_pseudo_inputs

(

self

)

def kusanagi.ghost.regression.GPRegressor.SPGP.loss_sp	(		self,
			X_sp
	)

def kusanagi.ghost.regression.GPRegressor.SPGP.predict_symbolic	(		self,
			mx,
			Sx
	)

def kusanagi.ghost.regression.GPRegressor.SPGP.set_dataset	(		self,
			X_dataset,
			Y_dataset
	)

def kusanagi.ghost.regression.GPRegressor.SPGP.set_state	(		self,
			state
	)

def kusanagi.ghost.regression.GPRegressor.SPGP.set_X_sp	(		self,
			X_sp
	)

def kusanagi.ghost.regression.GPRegressor.SPGP.train

(

self

)

Member Data Documentation

kusanagi.ghost.regression.GPRegressor.SPGP.Amm

kusanagi.ghost.regression.GPRegressor.SPGP.beta_sp

kusanagi.ghost.regression.GPRegressor.SPGP.dnlml_sp

kusanagi.ghost.regression.GPRegressor.SPGP.Lmm

kusanagi.ghost.regression.GPRegressor.SPGP.n_basis

kusanagi.ghost.regression.GPRegressor.SPGP.nlml_sp

kusanagi.ghost.regression.GPRegressor.SPGP.should_recompile

kusanagi.ghost.regression.GPRegressor.SPGP.X_sp

kusanagi.ghost.regression.GPRegressor.SPGP.X_sp_

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

• ghost/regression/GPRegressor.py