GitHub user actuaryzhang opened a pull request:
https://github.com/apache/spark/pull/17571
[SPARK-20258][Doc][SparkR] Fix SparkR logistic regression example in
programming guide (did not converge)
## What changes were proposed in this pull request?
SparkR logistic regression example did not converge in programming guide
(for IRWLS). All estimates are essentially zero:
```
training2 <- read.df("data/mllib/sample_binary_classification_data.txt",
source = "libsvm")
df_list2 <- randomSplit(training2, c(7,3), 2)
binomialDF <- df_list2[[1]]
binomialTestDF <- df_list2[[2]]
binomialGLM <- spark.glm(binomialDF, label ~ features, family = "binomial")
17/04/07 11:42:03 WARN WeightedLeastSquares: Cholesky solver failed due to
singular covariance matrix. Retrying with Quasi-Newton solver.
> summary(binomialGLM)
Coefficients:
Estimate
(Intercept) 9.0255e+00
features_0 0.0000e+00
features_1 0.0000e+00
features_2 0.0000e+00
features_3 0.0000e+00
features_4 0.0000e+00
features_5 0.0000e+00
features_6 0.0000e+00
features_7 0.0000e+00
```
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/actuaryzhang/spark programGuide2
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/17571.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #17571
----
commit 95b5383fae4da22aa0552e969c05b9488accb1a1
Author: actuaryzhang <actuaryzhan...@gmail.com>
Date: 2017-04-07T18:37:33Z
update logistic regression example
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