来自大数据的 Clojure 频率字典

Question

我想编写自己的朴素贝叶斯分类器我有一个这样的文件:

(这是垃圾邮件和火腿消息的数据库，第一个单词指向垃圾邮件或火腿，文本直到 eoln 是消息(大小:0.5 Mb)，来自此处http://www.dt.fee.unicamp.br/~tiago/smsspamcollection/)

ham     Go until jurong point, crazy.. Available only in bugis n gre
at world la e buffet... Cine there got amore wat...
ham     Ok lar... Joking wif u oni...
spam    Free entry in 2 a wkly comp to win FA Cup final tkts 21st May 2005. Text FA to 87121 to receive entry question(std txt rate)T&C's apply 08452810075over18's
ham     U dun say so early hor... U c already then say...
ham     Nah I don't think he goes to usf, he lives around here though
spam    FreeMsg Hey there darling it's been 3 week's now and no word back! I'd like some fun you up for it still? Tb ok! XxX std chgs to send, £1.50 to rcv

我想制作一个像这样的 HashMap :{“垃圾邮件”{“去”1，“直到”100，...}，“火腿”{......}} HashMap ，其中每个值都是单词的频率图(分别针对火腿和垃圾邮件)

我知道，如何通过python或c++做到这一点，我通过clojure做到了，但我的解决方案在大数据中失败了(stackoverflow)

我的解决方案:

(defn read_data_from_file [fname]
    (map #(split % #"\s")(map lower-case (with-open [rdr (reader fname)] 
        (doall (line-seq rdr))))))

(defn do-to-map [amap keyseq f]
    (reduce #(assoc %1 %2 (f (%1 %2))) amap keyseq))

(defn dicts_from_data [raw_data]
    (let [data (group-by #(first %) raw_data)]
        (do-to-map
            data (keys data) 
                (fn [x] (frequencies (reduce concat (map #(rest %) x)))))))

我试图找出错误的地方并写下这个

(def raw_data (read_data_from_file (first args)))
(def d (group-by #(first %) raw_data))
(def f (map frequencies raw_data))
(def d1 (reduce concat (d "spam")))
(println (reduce concat (d "ham")))

错误:

Exception in thread "main" java.lang.RuntimeException: java.lang.StackOverflowError
    at clojure.lang.Util.runtimeException(Util.java:165)
    at clojure.lang.Compiler.eval(Compiler.java:6476)
    at clojure.lang.Compiler.eval(Compiler.java:6455)
    at clojure.lang.Compiler.eval(Compiler.java:6431)
    at clojure.core$eval.invoke(core.clj:2795)
    at clojure.main$eval_opt.invoke(main.clj:296)
    at clojure.main$initialize.invoke(main.clj:315)
.....

有人可以帮助我让它变得更好/更有效吗？PS 抱歉我的写作错误。英语不是我的母语。

Answer 1

在匿名函数中使用 apply 而不是 reduce 可以避免 StackOverflow 异常。使用 (fn [x] (频率 (应用 concat (map #(rest %) x)))) 而不是 (fn [x] (frequencies) %) x)))).

以下是对相同的代码进行了一些重构，但具有完全相同的逻辑。 read-data-from-file 已更改，以避免两次mapping 行序列。

(use 'clojure.string)
(use 'clojure.java.io)

(defn read-data-from-file [fname]
  (let [lines (with-open [rdr (reader fname)] 
                (doall (line-seq rdr)))]
    (map #(-> % lower-case (split #"\s")) lines)))

(defn do-to-map [m keyseq f]
    (reduce #(assoc %1 %2 (f (%1 %2))) m keyseq))

(defn process-words [x]
  (->> x 
    (map #(rest %)) 
    (apply concat) ; This is the only real change from the 
                   ; original code, it used to be (reduce concat).
    frequencies))

(defn dicts-from-data [raw_data]
  (let [data (group-by first raw_data)]
    (do-to-map data
               (keys data) 
               process-words)))

(-> "SMSSpamCollection.txt" read-data-from-file dicts-from-data keys)