As per the Spark 2.1.0 documentation, Both HashingTF and CountVectorizer can be used to generate the term frequency vectors. HashingTF HashingTF is a Transformer which takes sets of terms and converts those sets into fixed-length feature vectors. In text processing, a “set of terms” might be a bag of words. HashingTF utilizes the hashing trick. A raw feature is mapped into an index (term) by apply
As it currently stands, this question is not a good fit for our Q&A format. We expect answers to be supported by facts, references, or expertise, but this question will likely solicit debate, arguments, polling, or extended discussion. If you feel that this question can be improved and possibly reopened, visit the help center for guidance. ANN (Artificial Neural Networks) and SVM (Support Vector M
Both C# and Scala have adopted frameworks for simplifying doing asynchronous/parallel computation, but in different ways. The latest C# (5.0, still in beta) has decided on an async/await framework (using continuation-passing under the hood, but in an easier-to-use way), while Scala instead uses the concept of "actors", and has recently taken the actors implementation in Akka and incorporated it in
Is there any difference between p and puts in Ruby?
hash = { "d" => [11, 22], "f" => [33, 44, 55] } # case 1 hash.map {|k,vs| vs.map {|v| "#{k}:#{v}"}}.join(",") => "d:11,d:22,f:33,f:44,f:55" # case 2 hash.map {|k,vs| vs.each {|v| "#{k}:#{v}"}}.join(",") => "11,22,33,44,55" only difference is case 1 uses vs.map, case 2 uses vs.each. What happened here?
What are the behavioural differences between the following two implementations in Ruby of the thrice method? module WithYield def self.thrice 3.times { yield } # yield to the implicit block argument end end module WithProcCall def self.thrice(&block) # & converts implicit block to an explicit, named Proc 3.times { block.call } # invoke Proc#call end end WithYield::thrice { puts "Hello world" } Wit
リリース、障害情報などのサービスのお知らせ
最新の人気エントリーの配信
処理を実行中です
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く