January 2019
Beginner to intermediate
576 pages
14h 31m
Chinese
Content preview from 深度學習｜內行人的做法
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深度學習在自然語言處理的應用
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251
使用段落向量，進行文件分類
就像本章稍早所提到的，我們可以在自然語言處理與文件分類等方面運用到段落向量。
在這裡的範例中，我們將使用類似前一個範例的一個段落向量模型，來構建出一個文件
分類器，幫我們從三個標籤中給出一個結果，輸出類似以下的內容：
Document 'health' falls into the following categories:
health: 0.29721372296220205
science: 0.011684473733853906
finance: -0.14755302887323793
正如你所看到的，分數最高的標籤就是我們的分類結果。我們就來看看範例 5-9 這個段
落向量分類應用（
http://bit.ly/2sOpJ5Q
）的程式碼吧。
範例
5-9
用段落向量來分類文件的
Java
程式碼
public class ParagraphVectorsClassifierExample {
ParagraphVectors paragraphVectors;
LabelAwareIterator iterator;
TokenizerFactory tokenizerFactory;
private static final Logger log =
LoggerFactory.getLogger(ParagraphVectorsClassifierExample.class);
public static void ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.