concrete.ml.sklearn.svm

module concrete.ml.sklearn.svm

Implement Support Vector Machine.

---

class LinearSVR

A Regression Support Vector Machine (SVM).

method __init__

__init__(
    n_bits=2,
    epsilon=0.0,
    tol=0.0001,
    C=1.0,
    loss='epsilon_insensitive',
    fit_intercept=True,
    intercept_scaling=1.0,
    dual=True,
    verbose=0,
    random_state=None,
    max_iter=1000
)

---

property fhe_circuit

Get the FHE circuit.

Returns:

• Circuit: the FHE circuit

---

property input_quantizers

Get the input quantizers.

Returns:

• List[QuantizedArray]: the input quantizers

---

property onnx_model

Get the ONNX model.

.. # noqa: DAR201

Returns:

• onnx.ModelProto: the ONNX model

---

property output_quantizers

Get the input quantizers.

Returns:

• List[QuantizedArray]: the input quantizers

---

property quantize_input

Get the input quantization function.

Returns:

• Callable : function that quantizes the input

---

class LinearSVC

A Classification Support Vector Machine (SVM).

method __init__

__init__(
    n_bits=2,
    penalty='l2',
    loss='squared_hinge',
    dual=True,
    tol=0.0001,
    C=1.0,
    multi_class='ovr',
    fit_intercept=True,
    intercept_scaling=1,
    class_weight=None,
    verbose=0,
    random_state=None,
    max_iter=1000
)

---

property fhe_circuit

Get the FHE circuit.

Returns:

• Circuit: the FHE circuit

---

property input_quantizers

Get the input quantizers.

Returns:

• List[QuantizedArray]: the input quantizers

---

property onnx_model

Get the ONNX model.

.. # noqa: DAR201

Returns:

• onnx.ModelProto: the ONNX model

---

property output_quantizers

Get the input quantizers.

Returns:

• List[QuantizedArray]: the input quantizers

---

property quantize_input

Get the input quantization function.

Returns:

• Callable : function that quantizes the input