[ https://issues.apache.org/jira/browse/SPARK-18374?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15662015#comment-15662015 ]
yuhao yang commented on SPARK-18374: ------------------------------------ With the default behavior of the _Tokenizer_ and _RegexTokenizer_, I think it's more reasonable to directly include words like _won't_, _haven't_ in the stop words lists, as shown in the list on http://www.ranks.nl/stopwords. More specifically, if a user is using the default _Tokenizer_ and _RegexTokenizer_ in spark.ml without customization, then _weren_, _wasn_ in current stop words list are useless,whereas _weren't_ and _wasn't_ can be helpful. The default behavior of ml transformers should be consistent and effective. > Incorrect words in StopWords/english.txt > ---------------------------------------- > > Key: SPARK-18374 > URL: https://issues.apache.org/jira/browse/SPARK-18374 > Project: Spark > Issue Type: Bug > Components: ML > Affects Versions: 2.0.1 > Reporter: nirav patel > > I was just double checking english.txt for list of stopwords as I felt it was > taking out valid tokens like 'won'. I think issue is english.txt list is > missing apostrophe character and all character after apostrophe. So "won't" > becam "won" in that list; "wouldn't" is "wouldn" . > Here are some incorrect tokens in this list: > won > wouldn > ma > mightn > mustn > needn > shan > shouldn > wasn > weren > I think ideal list should have both style. i.e. won't and wont both should be > part of english.txt as some tokenizer might remove special characters. But > 'won' is obviously shouldn't be in this list. > Here's list of snowball english stop words: > http://snowball.tartarus.org/algorithms/english/stop.txt -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org