} } }

    【题目和解决】NLTK was unable to find the megam file!(1)

    添加时间:2013-5-15 点击量:

    在学到“练习基于分类器的分块器”这一末节的时辰,在测试代码之后碰到了题目。



    class ConsecutiveNPChunkTagger(nltk.TaggerI):
    
    def __init__(self, train_sents):
    train_set
    = []
    for tagged_sent in train_sents:
    untagged_sent
    = nltk.tag.untag(tagged_sent)
    history
    = []
    for i, (word, tag) in enumerate(tagged_sent):
    featureset
    = npchunk_features(untagged_sent, i, history)
    train_set.append( (featureset, tag) )
    history.append(tag)
    self.classifier
    = nltk.MaxentClassifier.train(train_set, algorithm=megam, trace=0)
    def tag(self, sentence):
    history
    = []
    for i, word in enumerate(sentence):
    featureset
    = npchunk_features(sentence,i, history)
    tag
    = self.classifier.classify(featureset)
    history.append(tag)
    return zip(sentence, history)



    class ConsecutiveNPChunker(nltk.ChunkParserI):
    
    def __init__(self, train_sents):
    tagged_sents
    = [[((w,t),c) for (w,t,c) in
    nltk.chunk.tree2conlltags(sent)]
    for sent in train_sents]
    self.tagger
    = ConsecutiveNPChunkTagger(tagged_sents)
    def parse(self, sentence):
    tagged_sents
    = self.tagger.tag(sentence)
    conlltags
    =[(w,t,c) for ((w,t),c) in tagged_sents]
    return nltk.chunk.conlltags2tree(conlltags)




    def npchunk_features(sentence,i, history):
    
    ... word,pos
    = sentence[i]
    ...
    return {pos: pos}
    >>>chunker = ConsecutiveNPChunker(train_sents)
    >>>print chunker.evaluate(test_sents)


    以上是书上供给的代码,题目是,当在履行


    chunker = ConsecutiveNPChunker(train_sents)并没有如期履行,反而呈现了一个错误。


    Traceback (most recent call last):
    
    File
    <pyshell#119>, line 1, in <module>
    chunker
    = ConsecutiveNPChunker(train_sents)
    File
    <pyshell#118>, line 5, in __init__
    self.tagger
    = ConsecutiveNPChunkTagger(tagged_sents)
    File
    <pyshell#116>, line 11, in __init__
    self.classifier
    = nltk.MaxentClassifier.train(train_set, algorithm=megam, trace=0)
    File
    D:\SpecialSoftware\Python25\Lib\site-packages\nltk\classify\maxent.py, line 319, in train
    gaussian_prior_sigma,
    cutoffs)
    File
    D:\SpecialSoftware\Python25\Lib\site-packages\nltk\classify\maxent.py, line 1522, in train_maxent_classifier_with_megam
    stdout
    = call_megam(options)
    File
    D:\SpecialSoftware\Python25\Lib\site-packages\nltk\classify\megam.py, line 163, in call_megam
    config_megam()
    File
    D:\SpecialSoftware\Python25\Lib\site-packages\nltk\classify\megam.py, line 59, in config_megam
    url
    =http://www.cs.utah.edu/~hal/megam/
    File
    D:\SpecialSoftware\Python25\Lib\site-packages\nltk\internals.py, line 528, in find_binary
    url, verbose)
    File
    D:\SpecialSoftware\Python25\Lib\site-packages\nltk\internals.py, line 512, in find_file
    raise LookupError(\n\n%s\n%s\n%s (div, msg, div))
    LookupError:

    ===========================================================================
    NLTK was unable to find the megam file!
    Use software specific configuration paramaters
    or set the MEGAM environment variable.

    For more information, on megam, see:
    <http://www.cs.utah.edu/~hal/megam/>
    ===========================================================================


    固然说给出了响应的提示,然则并不完全。


    经由过程对谷歌的搜刮,找到了一些解决的端倪。


    我的操纵体系是Windows8.


    nltk说话对象的官网给出了提示:


    https://sites.google.com/site/naturallanguagetoolkit/download


    Megam为可选包,将来应用的时辰可以再来安装。的网址为:MegaM: http://hal3.name/megam/megam_src.tgz,直接我并没有成功,应用迅雷成功的。


    然则打开之后发明,都是些源文件。然则在这个紧缩包里面有一个README文件,给出了如何应用的提示,发明,还须要装一个器材。


    README中如许写到:ocaml(http://caml.inria.fr)


    须要到这个网站源文件的编译器,于是我了和本身电脑体系相匹配的版本,然则看申明安装起来还是须要揣摩的,在安装过程中提示是病毒,然则我还是选择信赖,要不然没办法持续。


     【如今Ocaml正在安装,我点的完全安装(可能实际傍边没有须要完全安装吧),等安装完成后,再持续摸索怎么解决这个题目】



     
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