FloatNonnegativeLeastSquares Class 
Namespace: CenterSpace.NMath.Core
The FloatNonnegativeLeastSquares type exposes the following members.
Name  Description  

FloatNonnegativeLeastSquares(FloatMatrix, FloatVector) 
Constructs a nonnegative least squares solution for the given linear system
Ax = y.
 
FloatNonnegativeLeastSquares(FloatMatrix, FloatVector, Boolean) 
Constructs a nonnegative least squares solution for the given linear system
Ax = y, optionally adding an intercept parameter to the
model.
 
FloatNonnegativeLeastSquares(FloatMatrix, FloatVector, Boolean, Single) 
Constructs a nonnegative least squares solution for the given linear system
Ax = y, optionally adding an intercept parameter to the
model.
 
FloatNonnegativeLeastSquares(FloatMatrix, FloatVector, Boolean, Single, Int32) 
Constructs a nonnegative least squares solution for the given linear system
Ax = y, optionally adding an intercept parameter to the
model.

Name  Description  

Iterations 
Gets the number of iterations performed by the algorithm.
 
MaxIterations 
Gets the maximum number of iterations performed by the algorithm.
Default is FloatNonnegativeLeastSquares.DEFAULT_MAX_ITERATIONS = 100000.
 
RankDeficiencyDetected 
If a rank deficiency was detected while solving an unconstrained
least squares problem during the nonnegative least squares iterative
algorithm, true is returned.
 
Residuals 
Gets the vector of residuals. If y is the righthand side of the
least squares equation Ax = y, and we denote by yhat the vector
Ax where x is the computed least squares solution,
then the vector of residuals r is the vector whose ith component is
r[i] = y[i]  yhat[i].
 
ResidualSumOfSquares 
Gets the residual sum of squares. If y is the righthand side of the
least squares equation Ax = y, and we denote by yhat the vector
Ax where x is the computed least squares solution,
then the residual sum of squares is defined to be
(y[0]  yhat[0])^2 + (y[1]  yhat[1])^2 + ... + (y[m1]  yhat[m1])^2.
 
Result 
Gets the result of the nonnegative least squares fit.
 
Tolerance 
Gets and sets the tolerance for detecting rank deficiency while
solving the nonnegative least squares problem. This number should be
"small" relative to the input data and within the precision of a
single precision number. Default value is
FloatNonnegativeLeastSquares.DEFAULT_TOLERANCE = 1e5F
 
X 
Gets the nonnegative least squares solution x for the least squares problem
Ax = y.
 
Yhat 
Gets the predicted value of y by computing yHat = Ax,
where x is the calculated solution to the least squares
problem Ax = y.

Name  Description  

Clone 
Creates a deep copy of this least squares.
 
SolveUnconstrainedLeastSq 
Method used to solve the unconstrained least squares problems,
Ax = y, generated by
the nonnegative least squares algorithm.

Name  Description  

DEFAULT_MAX_ITERATIONS 
Default maximum number of iterations to be performed by the algorithm.
 
DEFAULT_TOLERANCE 
The default tolerance for detecting rank deficiency while
solving the nonnegative least squares problem.
