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Implement component.fit, component.fit_xy

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This commit is contained in:
Alinson S. Xavier
2021-03-30 21:18:40 -05:00
parent 205a972937
commit 1224613b1a
7 changed files with 152 additions and 206 deletions
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19
miplearn/components/primal.py
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@@ -105,19 +105,11 @@ class PrimalSolutionComponent(Component):
) -> Dict[Hashable, np.ndarray]:
return self._build_x_y_dict(instances, self._extract_variable_features)
def y(
def fit_xy(
self,
instances: Union[List[str], List[Instance]],
) -> Dict[Hashable, np.ndarray]:
return self._build_x_y_dict(instances, self._extract_variable_labels)
def fit(
self,
training_instances: Union[List[str], List[Instance]],
n_jobs: int = 1,
x: Dict[str, np.ndarray],
y: Dict[str, np.ndarray],
) -> None:
x = self.x(training_instances)
y = self.y(training_instances)
for category in x.keys():
clf = self.classifier_factory()
thr = self.threshold_factory()
@@ -322,8 +314,11 @@ class PrimalSolutionComponent(Component):
x[category] = []
y[category] = []
features: Any = instance.get_variable_features(var, idx)
assert isinstance(features, list)
if "LP solution" in sample and sample["LP solution"] is not None:
features += [sample["LP solution"][var][idx]]
lp_value = sample["LP solution"][var][idx]
if lp_value is not None:
features += [sample["LP solution"][var][idx]]
x[category] += [features]
y[category] += [[opt_value < 0.5, opt_value >= 0.5]]
return x, y