lale.lib.autogen.kernel_ridge module

class lale.lib.autogen.kernel_ridge.KernelRidge(*, alpha=1, kernel='linear', gamma=None, degree=3, coef0=1, kernel_params=None)

Bases: PlannedIndividualOp

Combined schema for expected data and hyperparameters.

This documentation is auto-generated from JSON schemas.

Parameters

• alpha (integer, >=1 for optimizer, <=2 for optimizer, uniform distribution, default 1) – Small positive values of alpha improve the conditioning of the problem and reduce the variance of the estimates

• kernel (union type, default 'linear') –

  Kernel mapping used internally

  • callable, not for optimizer

  • or ‘linear’, ‘poly’, ‘precomputed’, ‘rbf’, or ‘sigmoid’

• gamma (union type, not for optimizer, default None) –

  Gamma parameter for the RBF, laplacian, polynomial, exponential chi2 and sigmoid kernels

  • float

  • or None

• degree (union type, default 3) –

  Degree of the polynomial kernel

  • integer, >=0 for optimizer, <=100 for optimizer, uniform distribution

  • or float, not for optimizer

• coef0 (float, >=0.0 for optimizer, <=1.0 for optimizer, uniform distribution, default 1) – Zero coefficient for polynomial and sigmoid kernels

• kernel_params (None, not for optimizer, default None) – Additional parameters (keyword arguments) for kernel function passed as callable object.

fit(X, y=None, **fit_params)

Train the operator.

Note: The fit method is not available until this operator is trainable.

Once this method is available, it will have the following signature:

Parameters

• X (array of items : array of items : float) – Training data

• y (union type) –

  Target values

  • array of items : float

  • or array of items : array of items : float

• sample_weight (union type, optional) –

  Individual weights for each sample, ignored if None is passed.

  • float

  • or array of items : float

predict(X, **predict_params)

Make predictions.

Note: The predict method is not available until this operator is trained.

Once this method is available, it will have the following signature:

Parameters

X (array of items : array of items : float) – Samples

Returns

result – Returns predicted values.

• array of items : float

• or array of items : array of items : float

Return type

union type