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Github user jkbradley commented on the issue: https://github.com/apache/spark/pull/19527 Thank you for all the work in this PR! Here's the follow-up: https://github.com/apache/spark/pull/20132 --- - To

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Github user jkbradley commented on the issue: https://github.com/apache/spark/pull/19527 Thanks for the updates! I still think there's some confusion, but since I think this code is correct & it doesn't affect APIs, I'll go ahead and merge this. I'll ping you on a follow-up PR to

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Github user jkbradley commented on the issue: https://github.com/apache/spark/pull/19527 @viirya Will you have time to update this soon? I'd like to get it in 2.3, which will mean merging it by Jan. 1. If you're busy, I can merge it as is and do a follow-up myself too. Thanks!

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Github user MLnick commented on the issue: https://github.com/apache/spark/pull/19527 Agree on keeping the new OneHotEncoderEstimator as an alias for 3.0 On Fri, 1 Dec 2017 at 23:29, jkbradley wrote: > *@jkbradley* commented on this pull

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Github user viirya commented on the issue: https://github.com/apache/spark/pull/19527 Ok, I understood. In other words, the extra category is added as the last category and `dropLast` option works as before. It makes sense to me. ---

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Github user jkbradley commented on the issue: https://github.com/apache/spark/pull/19527 > For example with 5 categories, we don't know [0.0, 0.0, 0.0, 0.0, 0.0] means last category or invalid value. For the semantics I described ("OPTION 1"), I think it is clear: * Last

[GitHub] spark issue #19527: [SPARK-13030][ML] Create OneHotEncoderEstimator for OneH...

Github user viirya commented on the issue: https://github.com/apache/spark/pull/19527 The behavior I thought is: * keep=true, dropLast=true ==> error option * keep=true, dropLast=false ==> vector size n (all-0 only for invalid value) For the cases of `dropLast =

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Github user jkbradley commented on the issue: https://github.com/apache/spark/pull/19527 Question about this PR description comment: > Note that keep can't be used at the same time with dropLast as true. Because they will conflict in encoded vector by producing a vector of zeros.

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Github user viirya commented on the issue: https://github.com/apache/spark/pull/19527 @BryanCutler @MLnick @WeichenXu123 Thanks for reviewing. Your comments should be all addressed now. Please take a look again when you have more time. ---

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Github user viirya commented on the issue: https://github.com/apache/spark/pull/19527 Benchmark against existing one hot encoder. Because existing encoder only needs to run `transform`, there is no fitting time. Transforming: numColums | Existing one

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Github user viirya commented on the issue: https://github.com/apache/spark/pull/19527 cc @MLnick @WeichenXu123 @jkbradley This adds a new class `OneHotEncoderEstimator` which extends `Estimator`. Please review this when you can. Thanks. ---

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