The BridgeRegression companion object defines hyper-parameters and factory methods.
Attributes
- Companion
- class
- Graph
-
- Supertypes
- Self type
-
BridgeRegression.type
Members list
Value members
Concrete methods
Create a Bridge Regression object from an xy matrix and center the data.
Create a Bridge Regression object from an xy matrix and center the data.
Value parameters
- col
-
the designated response column (defaults to the last column)
- fname
-
the feature/variable names (defaults to null)
- hparam
-
includes the shrinkage hyper-parameter
- xy
-
the uncentered data/input m-by-n matrix, NOT augmented with a first column of ones and the uncentered response m-vector (combined)
Attributes
Create a Bridge Regression object from an x matrix and y vector and center the data.
Create a Bridge Regression object from an x matrix and y vector and center the data.
Value parameters
- fname
-
the feature/variable names (defaults to null)
- hparam
-
includes the shrinkage hyper-parameter
- x
-
the uncentered data/input m-by-n matrix, NOT augmented with a first column of ones
- y
-
the uncentered response/output vector
Attributes
Create a Bridge Regression object from a data matrix and a response vector. This method provides data rescaling of x and centering of y.
Create a Bridge Regression object from a data matrix and a response vector. This method provides data rescaling of x and centering of y.
Value parameters
- fname
-
the feature/variable names (defaults to null)
- hparam
-
the shrinkage hyper-parameter (0 => OLS) in the penalty term 'lambda * norm b'
- x
-
the un-centered data/input m-by-n matrix, NOT augmented with a first column of ones
- y
-
the un-centered response/output vector