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      • concrete.ml.sklearn.base.md
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      • concrete.ml.sklearn.svm.md
      • concrete.ml.sklearn.tree.md
      • concrete.ml.sklearn.tree_to_numpy.md
      • concrete.ml.sklearn.xgb.md
      • concrete.ml.torch.compile.md
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  • module concrete.ml.sklearn.tree
  • class DecisionTreeClassifier
  • noqa: DAR101
  • class DecisionTreeRegressor
  • noqa: DAR101

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concrete.ml.sklearn.tree.md

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module concrete.ml.sklearn.tree

Implement DecisionTree models.


class DecisionTreeClassifier

Implements the sklearn DecisionTreeClassifier.

method __init__

__init__(
    criterion='gini',
    splitter='best',
    max_depth=None,
    min_samples_split=2,
    min_samples_leaf=1,
    min_weight_fraction_leaf=0.0,
    max_features=None,
    random_state=None,
    max_leaf_nodes=None,
    min_impurity_decrease=0.0,
    class_weight=None,
    ccp_alpha: float = 0.0,
    n_bits: int = 6
)

Initialize the DecisionTreeClassifier.

noqa: DAR101


property fhe_circuit

Get the FHE circuit.

The FHE circuit combines computational graph, mlir, client and server into a single object. More information available in Concrete documentation (https://docs.zama.ai/concrete/getting-started/terminology_and_structure) Is None if the model is not fitted.

Returns:

  • Circuit: The FHE circuit.


property is_compiled

Indicate if the model is compiled.

Returns:

  • bool: If the model is compiled.


property is_fitted

Indicate if the model is fitted.

Returns:

  • bool: If the model is fitted.


property n_classes_

Get the model's number of classes.

Using this attribute is deprecated.

Returns:

  • int: The model's number of classes.


property onnx_model

Get the ONNX model.

Is None if the model is not fitted.

Returns:

  • onnx.ModelProto: The ONNX model.


property target_classes_

Get the model's classes.

Using this attribute is deprecated.

Returns:

  • Optional[numpy.ndarray]: The model's classes.


method dump_dict

dump_dict() → Dict[str, Any]

classmethod load_dict

load_dict(metadata: Dict)

method post_processing

post_processing(y_preds: ndarray) → ndarray

class DecisionTreeRegressor

Implements the sklearn DecisionTreeClassifier.

method __init__

__init__(
    criterion='squared_error',
    splitter='best',
    max_depth=None,
    min_samples_split=2,
    min_samples_leaf=1,
    min_weight_fraction_leaf=0.0,
    max_features=None,
    random_state=None,
    max_leaf_nodes=None,
    min_impurity_decrease=0.0,
    ccp_alpha=0.0,
    n_bits: int = 6
)

Initialize the DecisionTreeRegressor.

noqa: DAR101


property fhe_circuit

Get the FHE circuit.

The FHE circuit combines computational graph, mlir, client and server into a single object. More information available in Concrete documentation (https://docs.zama.ai/concrete/getting-started/terminology_and_structure) Is None if the model is not fitted.

Returns:

  • Circuit: The FHE circuit.


property is_compiled

Indicate if the model is compiled.

Returns:

  • bool: If the model is compiled.


property is_fitted

Indicate if the model is fitted.

Returns:

  • bool: If the model is fitted.


property onnx_model

Get the ONNX model.

Is None if the model is not fitted.

Returns:

  • onnx.ModelProto: The ONNX model.


method dump_dict

dump_dict() → Dict[str, Any]

classmethod load_dict

load_dict(metadata: Dict)