lale.lib.autogen.lasso_lars module¶
- class lale.lib.autogen.lasso_lars.LassoLars(*, alpha=1.0, fit_intercept=True, verbose=False, precompute='auto', max_iter=500, eps=2.220446049250313e-16, copy_X=True, fit_path=True, positive=False)¶
Bases:
PlannedIndividualOp
Combined schema for expected data and hyperparameters.
This documentation is auto-generated from JSON schemas.
- Parameters
alpha (float, >=1e-10 for optimizer, <=1.0 for optimizer, loguniform distribution, default 1.0) – Constant that multiplies the penalty term
fit_intercept (boolean, default True) – whether to calculate the intercept for this model
verbose (union type, not for optimizer, default False) –
Sets the verbosity amount
boolean
or integer
precompute (union type, default 'auto') –
Whether to use a precomputed Gram matrix to speed up calculations
array, not for optimizer of items : Any
or ‘auto’
max_iter (integer, >=10 for optimizer, <=1000 for optimizer, uniform distribution, default 500) – Maximum number of iterations to perform.
eps (float, >=0.001 for optimizer, <=0.1 for optimizer, loguniform distribution, default 2.220446049250313e-16) – The machine-precision regularization in the computation of the Cholesky diagonal factors
copy_X (boolean, default True) – If True, X will be copied; else, it may be overwritten.
fit_path (boolean, not for optimizer, default True) – If
True
the full path is stored in thecoef_path_
attributepositive (boolean, default False) – Restrict coefficients to be >= 0
Notes
constraint-1 : any type
- 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
Xy (Any, optional) – Xy = np.dot(X.T, y) that can be precomputed
- 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 (union type) –
Samples.
array of items : Any
or array of items : array of items : float
- Returns
result – Returns predicted values.
- Return type
array of items : float