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author | Gary King <gary@idibon.com> | 2016-02-07 09:13:28 +0000 |
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committer | Sean Owen <sowen@cloudera.com> | 2016-02-07 09:13:28 +0000 |
commit | bc8890b357811612ba6c10d96374902b9e08134f (patch) | |
tree | de2ad39d76c48718a7faf5caa995ae6d259f51e2 /external/kafka | |
parent | 81da3bee669aaeb79ec68baaf7c99bff6e5d14fe (diff) | |
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[SPARK-13132][MLLIB] cache standardization param value in LogisticRegression
cache the value of the standardization Param in LogisticRegression, rather than re-fetching it from the ParamMap for every index and every optimization step in the quasi-newton optimizer
also, fix Param#toString to cache the stringified representation, rather than re-interpolating it on every call, so any other implementations that have similar repeated access patterns will see a benefit.
this change improves training times for one of my test sets from ~7m30s to ~4m30s
Author: Gary King <gary@idibon.com>
Closes #11027 from idigary/spark-13132-optimize-logistic-regression.
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