object LinearRegression extends Serializable
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def
apply(AInv: DenseMatrix[Double], vb: Seq[DenseVector[Double]]): DenseMatrix[Double]
Performs a multivariate linear regression on XA = B where the matrices A and B are given and X the matrix to solve for.
Performs a multivariate linear regression on XA = B where the matrices A and B are given and X the matrix to solve for.
- AInv
The (pseudo-) inverse of the matrix A
- vb
The columns of matrix B
- returns
Returns the matrix X that transforms A to B with minimal least squares errors.
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def
apply(va: Seq[DenseVector[Double]], vb: Seq[DenseVector[Double]], fv: Seq[(DenseVector[Double]) ⇒ DenseVector[Double]], invThreshold: Double): DenseMatrix[Double]
Performs a multivariate linear regression on XA = B where the matrices A and B are given and X the matrix to solve for.
Performs a multivariate linear regression on XA = B where the matrices A and B are given and X the matrix to solve for.
- va
The columns of matrix A
- vb
The columns of matrix B
- returns
Returns the matrix X that transforms A to B with minimal least squares errors.
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def
buildMatrixFromColumns(va: Seq[DenseVector[Double]], fv: Seq[(DenseVector[Double]) ⇒ DenseVector[Double]] = vectorMappingLinearFit): DenseMatrix[Double]
Builds the matrix A used in this linear regression implementation from its columns.
Builds the matrix A used in this linear regression implementation from its columns. The columns can be horizontally extended by horizontally concatenating multiple value-mapped versions of them which facilitates the fitting of higher order functions to given data.
The default behaviour of this function will generate a matrix of the following form:
/ | | ... | \ |va1 va2 ... va3| | | | ... | | \ 1 1 1 1 /
from the matrix colums stored in va. This matrix can be used for fitting a multilinear function.
- va
The columns
- fv
A sequence of one or more functions that will be applied to the column vectors before concatenation.
- returns
A matrix that can be used in the linear regression process.
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val
defaultInvThreshold: Double
Default threshold for inverting values in the process of computing the moore-penrose pseudo inverse.
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val
vectorMappingLinearFit: Seq[(DenseVector[Double]) ⇒ DenseVector[Double]]
Default vector mapping for the A matrix used in linear fitting.
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