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compute_log_marginal_likelihood(self)
Compute log marginal likelihood using self.train_fv and self.labels. |
source code
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Inherited from base.Classifier :
__str__ ,
clone ,
isTrained ,
predict ,
repredict ,
retrain ,
summary ,
train ,
trained
Inherited from misc.state.ClassWithCollections :
__getattribute__ ,
__new__ ,
__setattr__ ,
reset
Inherited from object :
__delattr__ ,
__hash__ ,
__reduce__ ,
__reduce_ex__
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predicted_variances = StateVariable(enabled= False, doc= "Vari...
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log_marginal_likelihood = StateVariable(enabled= False, doc= "...
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log_marginal_likelihood_gradient = StateVariable(enabled= Fals...
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_clf_internals = ['gpr', 'regression', 'retrainable']
Describes some specifics about the classifier -- is that it is
doing regression for instance....
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sigma_noise = Parameter(0.001, allowedtype= 'float', min= 1e-1...
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lm = Parameter(0.0, min= 0.0, allowedtype= 'float', doc= """Th...
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kernel = property(fget= lambda self: self.__kernel)
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Inherited from base.Classifier :
_DEV__doc__ ,
feature_ids ,
predicting_time ,
predictions ,
regression ,
retrainable ,
trained_dataset ,
trained_labels ,
trained_nsamples ,
training_confusion ,
training_time ,
values
Inherited from misc.state.ClassWithCollections :
descr
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