public static enum StochasticMultinomialLogisticRegression.Prior extends Enum<StochasticMultinomialLogisticRegression.Prior>
Enum Constant and Description |
---|
CAUCHY
This is a prior from the Cauchy (student-t) distribution, and it uses
the extra
alpha parameter. |
ELASTIC
This is the Elastic Net prior, and it uses the extra
alpha parameter. |
GAUSSIAN
A Gaussian prior, this is equivalent to L2 regularization.
|
LAPLACE
A Laplace prior, this is equivalent to L1 regularization
|
UNIFORM
This is the Uniform prior.
|
Modifier and Type | Method and Description |
---|---|
protected abstract double |
gradientError(double b_i,
double s_i) |
protected double |
gradientError(double b_i,
double s_i,
double alpha) |
protected abstract double |
logProb(double b_i,
double s_i) |
protected double |
logProb(double b_i,
double s_i,
double alpha) |
static StochasticMultinomialLogisticRegression.Prior |
valueOf(String name)
Returns the enum constant of this type with the specified name.
|
static StochasticMultinomialLogisticRegression.Prior[] |
values()
Returns an array containing the constants of this enum type, in
the order they are declared.
|
public static final StochasticMultinomialLogisticRegression.Prior GAUSSIAN
public static final StochasticMultinomialLogisticRegression.Prior LAPLACE
public static final StochasticMultinomialLogisticRegression.Prior ELASTIC
alpha
parameter. This prior is a mix of
both LAPLACE
and GAUSSIAN
. Alpha should be in the
range [0,1]. Alpha weight will be applied to the Laplace prior, and
(1-alpha) weight will be applied to the Gaussian prior. The extreme
values of this collapse into the Laplace and Gaussian priors.public static final StochasticMultinomialLogisticRegression.Prior CAUCHY
alpha
parameter. Alpha should be
in the range (0, Infty).public static final StochasticMultinomialLogisticRegression.Prior UNIFORM
public static StochasticMultinomialLogisticRegression.Prior[] values()
for (StochasticMultinomialLogisticRegression.Prior c : StochasticMultinomialLogisticRegression.Prior.values()) System.out.println(c);
public static StochasticMultinomialLogisticRegression.Prior valueOf(String name)
name
- the name of the enum constant to be returned.IllegalArgumentException
- if this enum type has no constant with the specified nameNullPointerException
- if the argument is nullprotected abstract double gradientError(double b_i, double s_i)
protected double gradientError(double b_i, double s_i, double alpha)
protected abstract double logProb(double b_i, double s_i)
protected double logProb(double b_i, double s_i, double alpha)
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