mlektic.methods.base package
Submodules
mlektic.methods.base.regularizers module
- class mlektic.methods.base.regularizers.Regularizers[source]
Bases:
objectA class that provides static methods for various types of regularization.
- l1(lambda_value: float) -> Callable[[tf.Tensor], tf.Tensor]
Returns a function that computes the L1 regularization term for a given tensor of weights.
- l2(lambda_value: float) -> Callable[[tf.Tensor], tf.Tensor]
Returns a function that computes the L2 regularization term for a given tensor of weights.
- elastic_net(lambda_value: float, alpha: float) -> Callable[[tf.Tensor], tf.Tensor]
Returns a function that computes the Elastic Net regularization term for a given tensor of weights.
- static elastic_net(lambda_value: float, alpha: float)[source]
Returns a function that computes the Elastic Net regularization term for a given tensor of weights.
- Parameters:
lambda_value (float) – The regularization parameter.
alpha (float) – The mixing parameter between L1 and L2 regularization, with 0 <= alpha <= 1.
- Returns:
A function that takes a tensor of weights as input and returns the Elastic Net regularization term.
- Return type:
Callable[[tf.Tensor], tf.Tensor]
- static l1(lambda_value: float)[source]
Returns a function that computes the L1 regularization term for a given tensor of weights.
- Parameters:
lambda_value (float) – The regularization parameter.
- Returns:
A function that takes a tensor of weights as input and returns the L1 regularization term.
- Return type:
Callable[[tf.Tensor], tf.Tensor]
- static l2(lambda_value: float)[source]
Returns a function that computes the L2 regularization term for a given tensor of weights.
- Parameters:
lambda_value (float) – The regularization parameter.
- Returns:
A function that takes a tensor of weights as input and returns the L2 regularization term.
- Return type:
Callable[[tf.Tensor], tf.Tensor]