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[SPARK-9911] [DOC] [ML] Update Userguide for Evaluator #8304
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I thought it is unnecessary to add a separate guide for evaluators and hence added a note within the existing example. |
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Test build #41221 has finished for PR 8304 at commit
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The `Evaluator` can be a [`RegressionEvaluator`](api/scala/index.html#org.apache.spark.ml.RegressionEvaluator) | ||
for regression problems, a [`BinaryClassificationEvaluator`](api/scala/index.html#org.apache.spark.ml.BinaryClassificationEvaluator) | ||
for binary data or a [`MultiClassClassificationEvaluator`](api/scala/index.html#org.apache.spark.ml.MultiClassClassificationEvaluator) |
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nit: Oxford comma ("...binary data, or a...")
+1 for @mengxr 's suggestion on JIRA to break this example into a separate |
That sounds like a great idea. But do you have better suggestions for an example? I would have to use a cross-validator and tune it anyway and I'm afraid there will be code repetition. |
I don't think we need code examples for every possible combination, otherwise combinatorial complexity is going to bite us hard. We can:
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lol. That is not what I had meant. Sorry I should be more clear from here on. In other words I was asking if it would be sufficient to move the Model Selection Example to the new |
Oh, sorry! I think moving the example and providing some guidance about how to choose evaluators/validators is sufficient for now. |
ping @jkbradley ? |
+1 for "moving the example and providing some guidance about how to choose evaluators/validators" Something simple, but separate, which we can build upon later on. |
@MechCoder is busy this week. I will make a PR based on this. |
Since all comments are minor (or beyond this PR), I'm going to merge this into master and branch-1.5 first and then send another PR to fix issues here and some others. |
I added a small note about the different types of evaluator and the metrics used.