Github user dbtsai commented on a diff in the pull request:
https://github.com/apache/spark/pull/17746#discussion_r113256277
--- Diff: R/pkg/inst/tests/testthat/test_mllib_classification.R ---
@@ -288,18 +288,18 @@ test_that("spark.mlp", {
c(0, 0, 0, 0, 0, 5, 5, 5, 5, 5, 9, 9, 9, 9, 9))
mlpPredictions <- collect(select(predict(model, mlpTestDF),
"prediction"))
expect_equal(head(mlpPredictions$prediction, 10),
- c("1.0", "1.0", "1.0", "1.0", "2.0", "1.0", "2.0", "2.0",
"1.0", "0.0"))
+ c("1.0", "1.0", "2.0", "1.0", "2.0", "1.0", "2.0", "2.0",
"1.0", "0.0"))
model <- spark.mlp(df, label ~ features, layers = c(4, 3), maxIter = 2,
initialWeights =
c(0.0, 0.0, 0.0, 0.0, 0.0, 5.0, 5.0, 5.0, 5.0, 5.0, 9.0, 9.0, 9.0,
9.0, 9.0))
mlpPredictions <- collect(select(predict(model, mlpTestDF),
"prediction"))
expect_equal(head(mlpPredictions$prediction, 10),
- c("1.0", "1.0", "1.0", "1.0", "2.0", "1.0", "2.0", "2.0",
"1.0", "0.0"))
+ c("1.0", "1.0", "2.0", "1.0", "2.0", "1.0", "2.0", "2.0",
"1.0", "0.0"))
model <- spark.mlp(df, label ~ features, layers = c(4, 3), maxIter = 2)
mlpPredictions <- collect(select(predict(model, mlpTestDF),
"prediction"))
expect_equal(head(mlpPredictions$prediction, 10),
- c("1.0", "1.0", "1.0", "1.0", "0.0", "1.0", "0.0", "2.0",
"1.0", "0.0"))
+ c("1.0", "1.0", "1.0", "1.0", "0.0", "1.0", "0.0", "0.0",
"1.0", "0.0"))
--- End diff --
With small datasets, it can result an ill-conditioned problem, which is not
ideal for unit-tests since they can be very unstable.
I wonder with real bigger datasets we use in scala unittests, with breeze
0.13.1, whether the number of iterations required for convergency are the same
compared with breeze 0.13?
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at infrastruct...@apache.org or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org
