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  • LibShortText 怎么处理中文文档

    LibShortText 是林智仁老师继 libsvm、liblinear 之后的另一力作,主要有几大特征:

    • It is more efficient than general text-mining packages. On a typical computer, processing and training 10 million short texts takes only around half an hour.
    • The fast training and testing is built upon the linear classifier LIBLINEAR
    • Default options often work well without tedious tuning.
    • An interactive tool for error analysis is included. Based on the property that each short text contains few words, LibShortText provides details in predicting each text.
    这么一个工具,如何使用在中文处理呢?
    尝试了一下中文的unigram feature的自动生成,发现中文character 没有count进unigram中=。=

    于是我发信问了作者
    作者回复:
    Unfortunately I don't think our code can now support Chinese
    documents.
    Chih-Jen

    但是,这完全是水平有限,对python不熟悉的后果,http://guoze.me/2014/09/25/libshorttext-introduction/ 这个链接里面,作者提出可以自己定制中文分词器来使程序work在中文上。
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  • 原文地址:https://www.cnblogs.com/zklidd/p/4079668.html
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