Trying to do doc classification in Spark. I am not sure what the hashing does in HashingTF; does it sacrifice any accuracy? I doubt it, but I don't know. The spark doc says it uses the "hashing trick"... just another example of really bad/confusing naming used by engineers (I'm guilty as well). CountVectorizer also requires setting the vocabulary size, but it has another parameter, a threshold par
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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
The purpose of PhoneGap is to allow HTML-based web applications to be deployed and installed as native applications. PhoneGap web applications are wrapped in a native application shell, and can be installed via the native app stores for multiple platforms. Additionally, PhoneGap strives to provide a common native API set which is typically unavailable to web applications, such as basic camera acce
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
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