Tobi Bosede created SPARK-17718:
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Summary: MLib Classification Documentation Update Needed
Key: SPARK-17718
URL: https://issues.apache.org/jira/browse/SPARK-17718
Project: Spark
Issue Type: Improvement
Reporter: Tobi Bosede
Priority: Minor
https://spark.apache.org/docs/1.6.0/mllib-linear-methods.html#mjx-eqn-eqregPrimal
The loss function here for logistic regression is confusing. It seems to imply
that spark uses only -1 and 1 class labels. However it uses 0,1. Note below
needs to make this point more visible to avoid confusion.
"Note that, in the mathematical formulation in this guide, a binary label
y is denoted as either +1 (positive) or −1 (negative), which is convenient
for the formulation. However, the negative label is represented by 0 in
spark.mllib instead of −1, to be consistent with multiclass labeling."
Better yet, the loss function should be replaced with that for 0, 1 despite
mathematical inconvenience, since that is what is actually implemented.
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