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- Added 10 new classifiers and regressors - Updated Documentation Signed-off-by: Arsh <[email protected]>
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,28 +1,79 @@ | ||
| from anai.utils.wrappers.classification_shell import ClassificationWrapper | ||
| from sklearn.linear_model import (PoissonRegressor, GammaRegressor, LassoLarsIC, | ||
| LassoLarsCV) | ||
| from sklearn.linear_model import (GammaRegressor, LassoLarsCV, LassoLarsIC, | ||
| OrthogonalMatchingPursuit, | ||
| OrthogonalMatchingPursuitCV, | ||
| PoissonRegressor, QuantileRegressor, | ||
| RANSACRegressor, TheilSenRegressor, | ||
| TweedieRegressor) | ||
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| class PoissonClassifier(ClassificationWrapper): | ||
| def __init__(self,num_classes=2, **params): | ||
| def __init__(self, num_classes=2, **params): | ||
| self.model = PoissonRegressor(**params) | ||
| self.num_classes = num_classes - 1 | ||
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| class GammaClassifier(ClassificationWrapper): | ||
| def __init__(self,num_classes=2, **params): | ||
| def __init__(self, num_classes=2, **params): | ||
| self.model = GammaRegressor(**params) | ||
| self.num_classes = num_classes - 1 | ||
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| class LassoLarsICClassifier(ClassificationWrapper): | ||
| def __init__(self,num_classes=2, **params): | ||
| def __init__(self, num_classes=2, **params): | ||
| self.model = LassoLarsIC(**params) | ||
| self.num_classes = num_classes - 1 | ||
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| class LassoLarsCVClassifier(ClassificationWrapper): | ||
| def __init__(self,num_classes=2, **params): | ||
| def __init__(self, num_classes=2, **params): | ||
| self.model = LassoLarsCV(**params) | ||
| self.num_classes = num_classes - 1 | ||
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| class TweedieClassifier(ClassificationWrapper): | ||
| def __init__(self, num_classes=2, **params): | ||
| self.model = TweedieRegressor(**params) | ||
| self.num_classes = num_classes - 1 | ||
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| # class GeneralizedLinearClassifier(ClassificationWrapper): | ||
| # def __init__(self,num_classes=2, **params): | ||
| # self.model = GeneralizedLinearRegressor(**params) | ||
| # self.num_classes = num_classes - 1 | ||
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| class RANSACClassifier(ClassificationWrapper): | ||
| def __init__(self, num_classes=2, **params): | ||
| self.model = RANSACRegressor(**params) | ||
| self.num_classes = num_classes - 1 | ||
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| class OrthogonalMatchingPursuitCVClassifier(ClassificationWrapper): | ||
| def __init__(self, num_classes=2, **params): | ||
| self.model = OrthogonalMatchingPursuitCV(**params) | ||
| self.num_classes = num_classes - 1 | ||
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| class OrthogonalMatchingPursuitClassifier(ClassificationWrapper): | ||
| def __init__(self, num_classes=2, **params): | ||
| self.model = OrthogonalMatchingPursuit(**params) | ||
| self.num_classes = num_classes - 1 | ||
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| # class AFMClassifier(ClassificationWrapper): | ||
| # def __init__(self,num_classes=2, **params): | ||
| # self.model = ComponentwiseGradientBoostingSurvivalAnalysis(**params) | ||
| # self.num_classes = num_classes - 1 | ||
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| class QuantileClassifier(ClassificationWrapper): | ||
| def __init__(self, num_classes=2, **params): | ||
| self.model = QuantileRegressor(**params) | ||
| self.num_classes = num_classes - 1 | ||
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| class TheilSenClassifier(ClassificationWrapper): | ||
| def __init__(self, num_classes=2, **params): | ||
| self.model = TheilSenRegressor(**params) | ||
| self.num_classes = num_classes - 1 |
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