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authorYanbo Liang <ybliang8@gmail.com>2016-07-19 12:31:04 +0100
committerSean Owen <sowen@cloudera.com>2016-07-19 12:31:04 +0100
commit670891496a82538a5e2bf981a4044fb6f4cbb062 (patch)
treea91eb7ad9962b2eb5f2de12e3522ec45aab951d1 /mllib/src/test/java/org/apache
parent5d92326be76cb15edc6e18e94a373e197f696803 (diff)
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[SPARK-16494][ML] Upgrade breeze version to 0.12
## What changes were proposed in this pull request? breeze 0.12 has been released for more than half a year, and it brings lots of new features, performance improvement and bug fixes. One of the biggest features is ```LBFGS-B``` which is an implementation of ```LBFGS``` with box constraints and much faster for some special case. We would like to implement Huber loss function for ```LinearRegression``` ([SPARK-3181](https://issues.apache.org/jira/browse/SPARK-3181)) and it requires ```LBFGS-B``` as the optimization solver. So we should bump up the dependent breeze version to 0.12. For more features, improvements and bug fixes of breeze 0.12, you can refer the following link: https://groups.google.com/forum/#!topic/scala-breeze/nEeRi_DcY5c ## How was this patch tested? No new tests, should pass the existing ones. Author: Yanbo Liang <ybliang8@gmail.com> Closes #14150 from yanboliang/spark-16494.
Diffstat (limited to 'mllib/src/test/java/org/apache')
-rw-r--r--mllib/src/test/java/org/apache/spark/ml/feature/JavaPCASuite.java6
1 files changed, 5 insertions, 1 deletions
diff --git a/mllib/src/test/java/org/apache/spark/ml/feature/JavaPCASuite.java b/mllib/src/test/java/org/apache/spark/ml/feature/JavaPCASuite.java
index ac479c0841..8c0338e284 100644
--- a/mllib/src/test/java/org/apache/spark/ml/feature/JavaPCASuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/feature/JavaPCASuite.java
@@ -107,7 +107,11 @@ public class JavaPCASuite extends SharedSparkSession {
.fit(df);
List<Row> result = pca.transform(df).select("pca_features", "expected").toJavaRDD().collect();
for (Row r : result) {
- Assert.assertEquals(r.get(1), r.get(0));
+ Vector calculatedVector = (Vector) r.get(0);
+ Vector expectedVector = (Vector) r.get(1);
+ for (int i = 0; i < calculatedVector.size(); i++) {
+ Assert.assertEquals(calculatedVector.apply(i), expectedVector.apply(i), 1.0e-8);
+ }
}
}
}