Package | Description |
---|---|
weka.classifiers.functions.pace |
Modifier and Type | Method and Description |
---|---|
PaceMatrix |
PaceMatrix.cbind(PaceMatrix b)
Returns a new matrix which binds two matrices with columns.
|
PaceMatrix |
MixtureDistribution.empiricalProbability(DoubleVector data,
PaceMatrix intervals)
Computes the empirical probabilities of the data over a set of
intervals.
|
abstract PaceMatrix |
MixtureDistribution.fittingIntervals(DoubleVector data)
Contructs the set of fitting intervals for mixture estimation.
|
PaceMatrix |
NormalMixture.fittingIntervals(DoubleVector data)
Contructs the set of fitting intervals for mixture estimation.
|
PaceMatrix |
ChisqMixture.fittingIntervals(DoubleVector data)
Contructs the set of fitting intervals for mixture estimation.
|
abstract PaceMatrix |
MixtureDistribution.probabilityMatrix(DoubleVector s,
PaceMatrix intervals)
Contructs the probability matrix for mixture estimation, given a set
of support points and a set of intervals.
|
PaceMatrix |
NormalMixture.probabilityMatrix(DoubleVector s,
PaceMatrix intervals)
Contructs the probability matrix for mixture estimation, given a set
of support points and a set of intervals.
|
PaceMatrix |
ChisqMixture.probabilityMatrix(DoubleVector s,
PaceMatrix intervals)
Contructs the probability matrix for mixture estimation, given a set
of support points and a set of intervals.
|
PaceMatrix |
PaceMatrix.rbind(PaceMatrix b)
Returns a new matrix which binds two matrices together with rows.
|
Modifier and Type | Method and Description |
---|---|
void |
PaceMatrix.backward(PaceMatrix b,
IntVector pvt,
int ks,
int k0)
Backward ordering of columns in terms of response explanation.
|
PaceMatrix |
PaceMatrix.cbind(PaceMatrix b)
Returns a new matrix which binds two matrices with columns.
|
double |
PaceMatrix.columnResponseExplanation(PaceMatrix b,
IntVector pvt,
int j,
int ks)
Returns the squared ks-th response value if the j-th column becomes
the ks-th after orthogonal transformation.
|
PaceMatrix |
MixtureDistribution.empiricalProbability(DoubleVector data,
PaceMatrix intervals)
Computes the empirical probabilities of the data over a set of
intervals.
|
void |
PaceMatrix.forward(PaceMatrix b,
IntVector pvt,
int k0)
Forward ordering of columns in terms of response explanation.
|
void |
PaceMatrix.h2(int j,
int k,
double q,
PaceMatrix b,
int l)
Performs single Householder transformation on one column of a matrix
|
int |
PaceMatrix.leastExplainingColumn(PaceMatrix b,
IntVector pvt,
int ks,
int k0)
Returns the index of the column that has the smallest (squared)
response, when the column is moved to become the (ks-1)-th
column.
|
void |
PaceMatrix.lsqr(PaceMatrix b,
IntVector pvt,
int k0)
QR transformation for a least squares problem
A x = b implicitly both A and b are transformed. |
void |
PaceMatrix.lsqrSelection(PaceMatrix b,
IntVector pvt,
int k0)
QR transformation for a least squares problem
A x = b implicitly both A and b are transformed. |
int |
PaceMatrix.mostExplainingColumn(PaceMatrix b,
IntVector pvt,
int ks)
Returns the index of the column that has the largest (squared)
response, when each of columns pvt[ks:] is moved to become the
ks-th column.
|
DoubleVector |
PaceMatrix.nnls(PaceMatrix b,
IntVector pvt)
Solves the nonnegative linear squares problem.
|
DoubleVector |
PaceMatrix.nnlse(PaceMatrix b,
PaceMatrix c,
PaceMatrix d,
IntVector pvt)
Solves the nonnegative least squares problem with equality
constraint.
|
DoubleVector |
PaceMatrix.nnlse1(PaceMatrix b,
IntVector pvt)
Solves the nonnegative least squares problem with equality
constraint.
|
void |
PaceMatrix.positiveDiagonal(PaceMatrix Y,
IntVector pvt)
Sets all diagonal elements to be positive (or nonnegative) without
changing the least squares solution
|
abstract PaceMatrix |
MixtureDistribution.probabilityMatrix(DoubleVector s,
PaceMatrix intervals)
Contructs the probability matrix for mixture estimation, given a set
of support points and a set of intervals.
|
PaceMatrix |
NormalMixture.probabilityMatrix(DoubleVector s,
PaceMatrix intervals)
Contructs the probability matrix for mixture estimation, given a set
of support points and a set of intervals.
|
PaceMatrix |
ChisqMixture.probabilityMatrix(DoubleVector s,
PaceMatrix intervals)
Contructs the probability matrix for mixture estimation, given a set
of support points and a set of intervals.
|
PaceMatrix |
PaceMatrix.rbind(PaceMatrix b)
Returns a new matrix which binds two matrices together with rows.
|
void |
PaceMatrix.rsolve(PaceMatrix b,
IntVector pvt,
int kp)
Solves upper-triangular equation
R x = b On output, the solution is stored in b |
void |
PaceMatrix.steplsqr(PaceMatrix b,
IntVector pvt,
int ks,
int j,
boolean adjoin)
Stepwise least squares QR-decomposition of the problem
A x = b
|
double |
PaceMatrix.times(int i,
int j0,
int j1,
PaceMatrix B,
int l)
Multiplication between a row (or part of a row) of the first matrix
and a column (or part or a column) of the second matrix.
|
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