Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/3022#discussion_r22061331
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/stat/impl/MultivariateGaussian.scala
---
@@ -0,0 +1,39 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.mllib.stat.impl
+
+import breeze.linalg.{DenseVector => BreezeVector, DenseMatrix =>
BreezeMatrix}
+import breeze.linalg.{Transpose, det, pinv}
+
+/**
+ * Utility class to implement the density function for multivariate
Gaussian distribution.
+ * Breeze provides this functionality, but it requires the Apache
Commons Math library,
+ * so this class is here so-as to not introduce a new dependency in
Spark.
+ */
+private[mllib] class MultivariateGaussian(
+ val mu: BreezeVector[Double],
+ val sigma: BreezeMatrix[Double]) extends Serializable {
+ private val sigmaInv2 = pinv(sigma) * -0.5
+ private val U = math.pow(2.0 * math.Pi, -mu.length / 2.0) *
math.pow(det(sigma), -0.5)
--- End diff --
By the way, ```det``` and ```pinv``` are factorizing the matrix twice. It
would be better to do one factorization (like SVD) and then compute the det and
inv from it. We can do that in a follow-up PR though.
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