From 1ba63d4163594a474ac658a7872064ab3aaf5f45 Mon Sep 17 00:00:00 2001 From: Itsuki Toyota Date: Sat, 22 Sep 2018 18:56:32 +0900 Subject: [PATCH] Increase iteration count for ldaModel.inference testing --- .../cloudml/zen/ml/clustering/LDASuite.scala | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/ml/src/test/scala/com/github/cloudml/zen/ml/clustering/LDASuite.scala b/ml/src/test/scala/com/github/cloudml/zen/ml/clustering/LDASuite.scala index 2220ff78..45d4df60 100644 --- a/ml/src/test/scala/com/github/cloudml/zen/ml/clustering/LDASuite.scala +++ b/ml/src/test/scala/com/github/cloudml/zen/ml/clustering/LDASuite.scala @@ -111,8 +111,8 @@ class LDASuite extends FunSuite with SharedSparkContext { val ldaModel = lda.toLDAModel.toLocalLDAModel data.collect().foreach { case (_, sv) => - val a = ldaModel.inference(sv) - val b = ldaModel.inference(sv) + val a = ldaModel.inference(sv, 100, 80) + val b = ldaModel.inference(sv, 100, 80) val sim: Double = euclideanDistance(a, b) assert(sim < 0.1) } @@ -145,8 +145,8 @@ class LDASuite extends FunSuite with SharedSparkContext { val ldaModel = lda.toLDAModel.toLocalLDAModel data.collect().foreach { case (_, sv) => - val a = ldaModel.inference(sv) - val b = ldaModel.inference(sv) + val a = ldaModel.inference(sv, 100, 80) + val b = ldaModel.inference(sv, 100, 80) val sim: Double = euclideanDistance(a, b) assert(sim < 0.1) } @@ -179,8 +179,8 @@ class LDASuite extends FunSuite with SharedSparkContext { val ldaModel = lda.toLDAModel.toLocalLDAModel data.collect().foreach { case (_, sv) => - val a = ldaModel.inference(sv) - val b = ldaModel.inference(sv) + val a = ldaModel.inference(sv, 100, 80) + val b = ldaModel.inference(sv, 100, 80) val sim: Double = euclideanDistance(a, b) assert(sim < 0.1) } @@ -213,8 +213,8 @@ class LDASuite extends FunSuite with SharedSparkContext { val ldaModel = lda.toLDAModel.toLocalLDAModel data.collect().foreach { case (_, sv) => - val a = ldaModel.inference(sv) - val b = ldaModel.inference(sv) + val a = ldaModel.inference(sv, 100, 80) + val b = ldaModel.inference(sv, 100, 80) val sim: Double = euclideanDistance(a, b) assert(sim < 0.1) }