diff options
Diffstat (limited to 'mllib-local/src/main/scala/org/apache/spark/ml/stat/distribution/MultivariateGaussian.scala')
| -rw-r--r-- | mllib-local/src/main/scala/org/apache/spark/ml/stat/distribution/MultivariateGaussian.scala | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/mllib-local/src/main/scala/org/apache/spark/ml/stat/distribution/MultivariateGaussian.scala b/mllib-local/src/main/scala/org/apache/spark/ml/stat/distribution/MultivariateGaussian.scala index 383d6d96e8..0be28677ef 100644 --- a/mllib-local/src/main/scala/org/apache/spark/ml/stat/distribution/MultivariateGaussian.scala +++ b/mllib-local/src/main/scala/org/apache/spark/ml/stat/distribution/MultivariateGaussian.scala @@ -47,7 +47,7 @@ class MultivariateGaussian @Since("2.0.0") ( this(Vectors.fromBreeze(mean), Matrices.fromBreeze(cov)) } - private val breezeMu = mean.toBreeze.toDenseVector + private val breezeMu = mean.asBreeze.toDenseVector /** * Compute distribution dependent constants: @@ -61,7 +61,7 @@ class MultivariateGaussian @Since("2.0.0") ( */ @Since("2.0.0") def pdf(x: Vector): Double = { - pdf(x.toBreeze) + pdf(x.asBreeze) } /** @@ -69,7 +69,7 @@ class MultivariateGaussian @Since("2.0.0") ( */ @Since("2.0.0") def logpdf(x: Vector): Double = { - logpdf(x.toBreeze) + logpdf(x.asBreeze) } /** Returns density of this multivariate Gaussian at given point, x */ @@ -113,7 +113,7 @@ class MultivariateGaussian @Since("2.0.0") ( * relation to the maximum singular value (same tolerance used by, e.g., Octave). */ private def calculateCovarianceConstants: (BDM[Double], Double) = { - val eigSym.EigSym(d, u) = eigSym(cov.toBreeze.toDenseMatrix) // sigma = u * diag(d) * u.t + val eigSym.EigSym(d, u) = eigSym(cov.asBreeze.toDenseMatrix) // sigma = u * diag(d) * u.t // For numerical stability, values are considered to be non-zero only if they exceed tol. // This prevents any inverted value from exceeding (eps * n * max(d))^-1 |