{"push_id":939880266,"size":1,"distinct_size":1,"ref":"refs/heads/branch-1.6","head":"8c2b67f55416562a0f1fafeefb073f79701c9cc9","before":"53184ce779d85022e49651e631df907dc75af045","commits":[{"sha":"8c2b67f55416562a0f1fafeefb073f79701c9cc9","author":{"email":"cc463b26613f4ba480f0f94ca5cb2cab678c4fcb@databricks.com","name":"Eric Liang"},"message":"[SPARK-12346][ML] Missing attribute names in GLM for vector-type features\n\nCurrently `summary()` fails on a GLM model fitted over a vector feature missing ML attrs, since the output feature attrs will also have no name. We can avoid this situation by forcing `VectorAssembler` to make up suitable names when inputs are missing names.\n\ncc mengxr\n\nAuthor: Eric Liang <ekl@databricks.com>\n\nCloses #10323 from ericl/spark-12346.\n\n(cherry picked from commit 5e492e9d5bc0992cbcffe64a9aaf3b334b173d2c)\nSigned-off-by: Xiangrui Meng <meng@databricks.com>","distinct":true,"url":"https://api.github.com/repos/apache/spark/commits/8c2b67f55416562a0f1fafeefb073f79701c9cc9"}]}