B C D E F G H I L M N P R S T U W

B

backward(PaceMatrix, IntVector, int, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
Backward ordering of columns in terms of response explanation.
buildClassifier(Instances) - Method in class weka.classifiers.functions.PaceRegression
Builds a pace regression model for the given data.

C

cbind(PaceMatrix) - Method in class weka.classifiers.functions.pace.PaceMatrix
Returns a new matrix which binds two matrices with columns.
checkForMissing(Instance, Instances) - Method in class weka.classifiers.functions.PaceRegression
Checks if an instance has a missing value.
ChisqMixture - Class in weka.classifiers.functions.pace
Class for manipulating chi-square mixture distributions.
ChisqMixture() - Constructor for class weka.classifiers.functions.pace.ChisqMixture
Contructs an empty ChisqMixture
classifyInstance(Instance) - Method in class weka.classifiers.functions.PaceRegression
Classifies the given instance using the linear regression function.
clone() - Method in class weka.classifiers.functions.pace.DiscreteFunction
Clones the discrete function
clone() - Method in class weka.classifiers.functions.pace.PaceMatrix
Clone the PaceMatrix object.
coefficients() - Method in class weka.classifiers.functions.PaceRegression
Returns the coefficients for this linear model.
columnResponseExplanation(PaceMatrix, IntVector, int, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
Returns the squared ks-th response value if the j-th column becomes the ks-th after orthogonal transformation.

D

debugTipText() - Method in class weka.classifiers.functions.PaceRegression
Returns the tip text for this property
DiscreteFunction - Class in weka.classifiers.functions.pace
Class for handling discrete functions.
DiscreteFunction() - Constructor for class weka.classifiers.functions.pace.DiscreteFunction
Constructs an empty discrete function
DiscreteFunction(DoubleVector) - Constructor for class weka.classifiers.functions.pace.DiscreteFunction
Constructs a discrete function with the point values provides and the function values are all 1/n.
DiscreteFunction(DoubleVector, DoubleVector) - Constructor for class weka.classifiers.functions.pace.DiscreteFunction
Constructs a discrete function with both the point values and function values provided.

E

empiricalBayesEstimate(double) - Method in class weka.classifiers.functions.pace.NormalMixture
Returns the empirical Bayes estimate of a single value.
empiricalBayesEstimate(DoubleVector) - Method in class weka.classifiers.functions.pace.NormalMixture
Returns the empirical Bayes estimate of a vector.
empiricalProbability(DoubleVector, PaceMatrix) - Method in class weka.classifiers.functions.pace.MixtureDistribution
Computes the empirical probabilities of the data over a set of intervals.
estimatorTipText() - Method in class weka.classifiers.functions.PaceRegression
Returns the tip text for this property

F

f(double) - Method in class weka.classifiers.functions.pace.ChisqMixture
Computes the value of f(x) given the mixture.
f(DoubleVector) - Method in class weka.classifiers.functions.pace.ChisqMixture
Computes the value of f(x) given the mixture, where x is a vector.
f(double) - Method in class weka.classifiers.functions.pace.NormalMixture
Computes the value of f(x) given the mixture.
f(DoubleVector) - Method in class weka.classifiers.functions.pace.NormalMixture
Computes the value of f(x) given the mixture, where x is a vector.
fit(DoubleVector) - Method in class weka.classifiers.functions.pace.MixtureDistribution
Fits the mixture (or mixing) distribution to the data.
fit(DoubleVector, int) - Method in class weka.classifiers.functions.pace.MixtureDistribution
Fits the mixture (or mixing) distribution to the data.
fitForSingleCluster(DoubleVector, int) - Method in class weka.classifiers.functions.pace.MixtureDistribution
Fits the mixture (or mixing) distribution to the data.
fittingIntervals(DoubleVector) - Method in class weka.classifiers.functions.pace.ChisqMixture
Contructs the set of fitting intervals for mixture estimation.
fittingIntervals(DoubleVector) - Method in class weka.classifiers.functions.pace.MixtureDistribution
Contructs the set of fitting intervals for mixture estimation.
fittingIntervals(DoubleVector) - Method in class weka.classifiers.functions.pace.NormalMixture
Contructs the set of fitting intervals for mixture estimation.
forward(PaceMatrix, IntVector, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
Forward ordering of columns in terms of response explanation.

G

g1(double, double) - Method in class weka.classifiers.functions.pace.PaceMatrix
Constructs the Givens rotation
g2(double[], int, int, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
Performs the Givens rotation
getCapabilities() - Method in class weka.classifiers.functions.PaceRegression
Returns default capabilities of the classifier.
getColumn(int) - Method in class weka.classifiers.functions.pace.PaceMatrix
Return a DoubleVector that stores a column of the matrix
getColumn(int, int, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
Return a DoubleVector that stores some elements of a column of the matrix
getDebug() - Method in class weka.classifiers.functions.PaceRegression
Controls whether debugging output will be printed
getEstimator() - Method in class weka.classifiers.functions.PaceRegression
Gets the estimator
getFunctionValue(int) - Method in class weka.classifiers.functions.pace.DiscreteFunction
Gets a particular function value
getMixingDistribution() - Method in class weka.classifiers.functions.pace.MixtureDistribution
Gets the mixing distribution
getOptions() - Method in class weka.classifiers.functions.PaceRegression
Gets the current settings of the classifier.
getPointValue(int) - Method in class weka.classifiers.functions.pace.DiscreteFunction
Gets a particular point value
getRevision() - Method in class weka.classifiers.functions.pace.ChisqMixture
Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.pace.DiscreteFunction
Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.pace.NormalMixture
Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.pace.PaceMatrix
Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.PaceRegression
Returns the revision string.
getSeparatingThreshold() - Method in class weka.classifiers.functions.pace.ChisqMixture
Gets the separating threshold value.
getSeparatingThreshold() - Method in class weka.classifiers.functions.pace.NormalMixture
Gets the separating threshold value.
getTechnicalInformation() - Method in class weka.classifiers.functions.pace.MixtureDistribution
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.functions.PaceRegression
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getThreshold() - Method in class weka.classifiers.functions.PaceRegression
Gets the threshold for olsc estimator
getTrimingThreshold() - Method in class weka.classifiers.functions.pace.ChisqMixture
Gets the triming thresholding value.
getTrimingThreshold() - Method in class weka.classifiers.functions.pace.NormalMixture
Gets the triming thresholding value.
globalInfo() - Method in class weka.classifiers.functions.PaceRegression
Returns a string describing this classifier

H

h(double) - Method in class weka.classifiers.functions.pace.ChisqMixture
Computes the value of h(x) given the mixture.
h(DoubleVector) - Method in class weka.classifiers.functions.pace.ChisqMixture
Computes the value of h(x) given the mixture, where x is a vector.
h(double) - Method in class weka.classifiers.functions.pace.NormalMixture
Computes the value of h(x) given the mixture.
h(DoubleVector) - Method in class weka.classifiers.functions.pace.NormalMixture
Computes the value of h(x) given the mixture, where x is a vector.
h1(int, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
Constructs single Householder transformation for a column
h2(int, int, double, PaceMatrix, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
Performs single Householder transformation on one column of a matrix
hf(double) - Method in class weka.classifiers.functions.pace.ChisqMixture
Computes the value of h(x) / f(x) given the mixture.
hf(double) - Method in class weka.classifiers.functions.pace.NormalMixture
Computes the value of h(x) / f(x) given the mixture.

I

isEmpty() - Method in class weka.classifiers.functions.pace.DiscreteFunction
Returns true if it is empty.
isEmpty() - Method in class weka.classifiers.functions.pace.PaceMatrix
Check if the matrix is empty

L

leastExplainingColumn(PaceMatrix, IntVector, int, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
Returns the index of the column that has the smallest (squared) response, when the column is moved to become the (ks-1)-th column.
listOptions() - Method in class weka.classifiers.functions.PaceRegression
Returns an enumeration describing the available options.
lsqr(PaceMatrix, IntVector, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
QR transformation for a least squares problem
A x = b
implicitly both A and b are transformed.
lsqrSelection(PaceMatrix, IntVector, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
QR transformation for a least squares problem
A x = b
implicitly both A and b are transformed.

M

main(String[]) - Static method in class weka.classifiers.functions.pace.ChisqMixture
Method to test this class
main(String[]) - Static method in class weka.classifiers.functions.pace.DiscreteFunction
 
main(String[]) - Static method in class weka.classifiers.functions.pace.NormalMixture
Method to test this class
main(String[]) - Static method in class weka.classifiers.functions.pace.PaceMatrix
for testing only
main(String[]) - Static method in class weka.classifiers.functions.PaceRegression
Generates a linear regression function predictor.
maxAbs() - Method in class weka.classifiers.functions.pace.PaceMatrix
Returns the maximum absolute value of all elements
maxAbs(int, int, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
Returns the maximum absolute value of some elements of a column, that is, the elements of A[i0:i1][j].
minAbs(int, int, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
Returns the minimum absolute value of some elements of a column, that is, the elements of A[i0:i1][j].
MixtureDistribution - Class in weka.classifiers.functions.pace
Abtract class for manipulating mixture distributions.
MixtureDistribution() - Constructor for class weka.classifiers.functions.pace.MixtureDistribution
 
mostExplainingColumn(PaceMatrix, IntVector, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
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.

N

nestedEstimate(DoubleVector) - Method in class weka.classifiers.functions.pace.NormalMixture
Returns the optimal nested model estimate of a vector.
nnls(PaceMatrix, IntVector) - Method in class weka.classifiers.functions.pace.PaceMatrix
Solves the nonnegative linear squares problem.
nnlse(PaceMatrix, PaceMatrix, PaceMatrix, IntVector) - Method in class weka.classifiers.functions.pace.PaceMatrix
Solves the nonnegative least squares problem with equality constraint.
nnlse1(PaceMatrix, IntVector) - Method in class weka.classifiers.functions.pace.PaceMatrix
Solves the nonnegative least squares problem with equality constraint.
NNMMethod - Static variable in class weka.classifiers.functions.pace.MixtureDistribution
The nonnegative-measure-based method
normalize() - Method in class weka.classifiers.functions.pace.DiscreteFunction
Normalizes the function values with L1-norm.
NormalMixture - Class in weka.classifiers.functions.pace
Class for manipulating normal mixture distributions.
NormalMixture() - Constructor for class weka.classifiers.functions.pace.NormalMixture
Contructs an empty NormalMixture
numParameters() - Method in class weka.classifiers.functions.PaceRegression
Get the number of coefficients used in the model

P

pace2(DoubleVector) - Method in class weka.classifiers.functions.pace.ChisqMixture
Returns the pace2 estimate of a vector.
pace4(DoubleVector) - Method in class weka.classifiers.functions.pace.ChisqMixture
Returns the pace4 estimate of a vector.
pace6(double) - Method in class weka.classifiers.functions.pace.ChisqMixture
Returns the pace6 estimate of a single value.
pace6(DoubleVector) - Method in class weka.classifiers.functions.pace.ChisqMixture
Returns the pace6 estimate of a vector.
PaceMatrix - Class in weka.classifiers.functions.pace
Class for matrix manipulation used for pace regression.
PaceMatrix(int, int) - Constructor for class weka.classifiers.functions.pace.PaceMatrix
Construct an m-by-n PACE matrix of zeros.
PaceMatrix(int, int, double) - Constructor for class weka.classifiers.functions.pace.PaceMatrix
Construct an m-by-n constant PACE matrix.
PaceMatrix(double[][]) - Constructor for class weka.classifiers.functions.pace.PaceMatrix
Construct a PACE matrix from a 2-D array.
PaceMatrix(double[][], int, int) - Constructor for class weka.classifiers.functions.pace.PaceMatrix
Construct a PACE matrix quickly without checking arguments.
PaceMatrix(double[], int) - Constructor for class weka.classifiers.functions.pace.PaceMatrix
Construct a PaceMatrix from a one-dimensional packed array
PaceMatrix(DoubleVector) - Constructor for class weka.classifiers.functions.pace.PaceMatrix
Construct a PaceMatrix with a single column from a DoubleVector
PaceMatrix(Matrix) - Constructor for class weka.classifiers.functions.pace.PaceMatrix
Construct a PaceMatrix from a Matrix
PaceRegression - Class in weka.classifiers.functions
Class for building pace regression linear models and using them for prediction.
PaceRegression() - Constructor for class weka.classifiers.functions.PaceRegression
 
plus(DiscreteFunction) - Method in class weka.classifiers.functions.pace.DiscreteFunction
Returns the combined of two discrete functions
plusEquals(DiscreteFunction) - Method in class weka.classifiers.functions.pace.DiscreteFunction
Returns the combined of two discrete functions.
PMMethod - Static variable in class weka.classifiers.functions.pace.MixtureDistribution
The probability-measure-based method
positiveDiagonal(PaceMatrix, IntVector) - Method in class weka.classifiers.functions.pace.PaceMatrix
Sets all diagonal elements to be positive (or nonnegative) without changing the least squares solution
probabilityMatrix(DoubleVector, PaceMatrix) - Method in class weka.classifiers.functions.pace.ChisqMixture
Contructs the probability matrix for mixture estimation, given a set of support points and a set of intervals.
probabilityMatrix(DoubleVector, PaceMatrix) - Method in class weka.classifiers.functions.pace.MixtureDistribution
Contructs the probability matrix for mixture estimation, given a set of support points and a set of intervals.
probabilityMatrix(DoubleVector, PaceMatrix) - Method in class weka.classifiers.functions.pace.NormalMixture
Contructs the probability matrix for mixture estimation, given a set of support points and a set of intervals.

R

randomNormal(int, int) - Static method in class weka.classifiers.functions.pace.PaceMatrix
Generate matrix with standard-normally distributed random elements
rbind(PaceMatrix) - Method in class weka.classifiers.functions.pace.PaceMatrix
Returns a new matrix which binds two matrices together with rows.
rsolve(PaceMatrix, IntVector, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
Solves upper-triangular equation
R x = b
On output, the solution is stored in b

S

separable(DoubleVector, int, int, double) - Method in class weka.classifiers.functions.pace.ChisqMixture
Return true if a value can be considered for mixture estimation separately from the data indexed between i0 and i1
separable(DoubleVector, int, int, double) - Method in class weka.classifiers.functions.pace.MixtureDistribution
Return true if a value can be considered for mixture estimatino separately from the data indexed between i0 and i1
separable(DoubleVector, int, int, double) - Method in class weka.classifiers.functions.pace.NormalMixture
Return true if a value can be considered for mixture estimatino separately from the data indexed between i0 and i1
setColumnDimension(int) - Method in class weka.classifiers.functions.pace.PaceMatrix
Set the column dimenion of the matrix
setDebug(boolean) - Method in class weka.classifiers.functions.PaceRegression
Controls whether debugging output will be printed
setEstimator(SelectedTag) - Method in class weka.classifiers.functions.PaceRegression
Sets the estimator.
setFunctionValue(int, double) - Method in class weka.classifiers.functions.pace.DiscreteFunction
Sets a particular function value
setMatrix(int, int, int, int, double) - Method in class weka.classifiers.functions.pace.PaceMatrix
Set the submatrix A[i0:i1][j0:j1] with a same value
setMatrix(int, int, int, DoubleVector) - Method in class weka.classifiers.functions.pace.PaceMatrix
Set the submatrix A[i0:i1][j] with the values stored in a DoubleVector
setMatrix(double[], boolean) - Method in class weka.classifiers.functions.pace.PaceMatrix
Set the whole matrix from a 1-D array
setMixingDistribution(DiscreteFunction) - Method in class weka.classifiers.functions.pace.MixtureDistribution
Sets the mixing distribution
setOptions(String[]) - Method in class weka.classifiers.functions.PaceRegression
Parses a given list of options.
setPlus(int, int, double) - Method in class weka.classifiers.functions.pace.PaceMatrix
Add a value to an element and reset the element
setPointValue(int, double) - Method in class weka.classifiers.functions.pace.DiscreteFunction
Sets a particular point value
setRowDimension(int) - Method in class weka.classifiers.functions.pace.PaceMatrix
Set the row dimenion of the matrix
setSeparatingThreshold(double) - Method in class weka.classifiers.functions.pace.ChisqMixture
Sets the separating threshold value
setSeparatingThreshold(double) - Method in class weka.classifiers.functions.pace.NormalMixture
Sets the separating threshold value
setThreshold(double) - Method in class weka.classifiers.functions.PaceRegression
Set threshold for the olsc estimator
setTimes(int, int, double) - Method in class weka.classifiers.functions.pace.PaceMatrix
Multiply a value with an element and reset the element
setTrimingThreshold(double) - Method in class weka.classifiers.functions.pace.ChisqMixture
Sets the triming thresholding value.
setTrimingThreshold(double) - Method in class weka.classifiers.functions.pace.NormalMixture
Sets the triming thresholding value.
size() - Method in class weka.classifiers.functions.pace.DiscreteFunction
Returns the size of the point set.
sort() - Method in class weka.classifiers.functions.pace.DiscreteFunction
Sorts the point values of the discrete function.
steplsqr(PaceMatrix, IntVector, int, int, boolean) - Method in class weka.classifiers.functions.pace.PaceMatrix
Stepwise least squares QR-decomposition of the problem A x = b
subsetEstimate(DoubleVector) - Method in class weka.classifiers.functions.pace.NormalMixture
Returns the estimate of optimal subset selection.
sum2(int, int, int, boolean) - Method in class weka.classifiers.functions.pace.PaceMatrix
Squared sum of a column or row in a matrix
sum2(boolean) - Method in class weka.classifiers.functions.pace.PaceMatrix
Squared sum of columns or rows of a matrix
supportPoints(DoubleVector, int) - Method in class weka.classifiers.functions.pace.ChisqMixture
Contructs the set of support points for mixture estimation.
supportPoints(DoubleVector, int) - Method in class weka.classifiers.functions.pace.MixtureDistribution
Contructs the set of support points for mixture estimation.
supportPoints(DoubleVector, int) - Method in class weka.classifiers.functions.pace.NormalMixture
Contructs the set of support points for mixture estimation.

T

TAGS_ESTIMATOR - Static variable in class weka.classifiers.functions.PaceRegression
estimator types
thresholdTipText() - Method in class weka.classifiers.functions.PaceRegression
Returns the tip text for this property
times(int, int, int, PaceMatrix, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
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.
timesEquals(double) - Method in class weka.classifiers.functions.pace.DiscreteFunction
All function values are multiplied by a double
toString() - Method in class weka.classifiers.functions.pace.ChisqMixture
Converts to a string
toString() - Method in class weka.classifiers.functions.pace.DiscreteFunction
Converts the discrete function to string.
toString() - Method in class weka.classifiers.functions.pace.MixtureDistribution
Converts to a string
toString() - Method in class weka.classifiers.functions.pace.NormalMixture
Converts to a string
toString() - Method in class weka.classifiers.functions.pace.PaceMatrix
Converts matrix to string
toString(int, boolean) - Method in class weka.classifiers.functions.pace.PaceMatrix
Converts matrix to string
toString() - Method in class weka.classifiers.functions.PaceRegression
Outputs the linear regression model as a string.
trim(DoubleVector) - Method in class weka.classifiers.functions.pace.ChisqMixture
Trims the small values of the estaimte
trim(DoubleVector) - Method in class weka.classifiers.functions.pace.NormalMixture
Trims the small values of the estaimte

U

unique() - Method in class weka.classifiers.functions.pace.DiscreteFunction
Makes each individual point value unique

W

weka.classifiers.functions - package weka.classifiers.functions
 
weka.classifiers.functions.pace - package weka.classifiers.functions.pace
 

B C D E F G H I L M N P R S T U W