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[#186] fixed distribution across files and added base class for reusability

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Max Zwiessele 2015-09-11 17:13:21 +01:00
parent 69f6cfa6f7
commit 383cf41dab
4 changed files with 128 additions and 153 deletions
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7
GPy/models/sparse_gp_classification.py
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@ -6,8 +6,7 @@ import numpy as np
from ..core import SparseGP
from .. import likelihoods
from .. import kern
from ..likelihoods import likelihood
from ..inference.latent_function_inference import expectation_propagation_dtc
from ..inference.latent_function_inference import EPDTC
class SparseGPClassification(SparseGP):
"""
@ -39,7 +38,7 @@ class SparseGPClassification(SparseGP):
else:
assert Z.shape[1] == X.shape[1]
SparseGP.__init__(self, X, Y, Z, kernel, likelihood, inference_method=expectation_propagation_dtc.EPDTC(), name='SparseGPClassification',Y_metadata=Y_metadata)
SparseGP.__init__(self, X, Y, Z, kernel, likelihood, inference_method=EPDTC(), name='SparseGPClassification',Y_metadata=Y_metadata)
class SparseGPClassificationUncertainInput(SparseGP):
"""
@ -78,7 +77,7 @@ class SparseGPClassificationUncertainInput(SparseGP):
X = NormalPosterior(X, X_variance)
SparseGP.__init__(self, X, Y, Z, kernel, likelihood,
inference_method=expectation_propagation_dtc.EPDTC(),
inference_method=EPDTC(),
name='SparseGPClassification', Y_metadata=Y_metadata, normalizer=normalizer)
def parameters_changed(self):