我想基于遵循 Zipf 分布的单词(来自字典)创建数据源(用 Java 编写)。所以我来到了Apache commons 库的ZipfDistribution和NormalDistribution 。不幸的是,有关如何使用这些类的信息很少。我尝试做一些测试,但我不确定我是否以正确的方式使用它。我仅遵循每个构造函数的文档中所写的内容。但结果似乎并不“分布均匀”。import org.apache.commons.math3.distribution.NormalDistribution;import org.apache.commons.math3.distribution.ZipfDistribution;import java.io.BufferedReader;import java.io.IOException;import java.io.InputStream;import java.io.InputStreamReader;import java.net.URL;public class ZipfDistributionDataSource extends RichSourceFunction<String> { private static final String DISTINCT_WORDS_URL = "https://raw.githubusercontent.com/dwyl/english-words/master/words_alpha.txt"; public static void main(String[] args) throws Exception { ZipfDistributionDataSource zipfDistributionDataSource = new ZipfDistributionDataSource(); StringBuffer stringBuffer = new StringBuffer(zipfDistributionDataSource.readDataFromResource()); String[] words = stringBuffer.toString().split("\n"); System.out.println("size: " + words.length); System.out.println("Normal Distribution"); NormalDistribution normalDistribution = new NormalDistribution(words.length / 2, 1); for (int i = 0; i < 10; i++) { int sample = (int) normalDistribution.sample(); System.out.print("sample[" + sample + "]: "); System.out.println(words[sample]); } System.out.println(); System.out.println("Zipf Distribution"); ZipfDistribution zipfDistribution = new ZipfDistribution(words.length - 1, 1); for (int i = 0; i < 10; i++) { int sample = zipfDistribution.sample(); System.out.print("sample[" + sample + "]: "); System.out.println(words[sample]); } }
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青春有我
TA贡献1784条经验 获得超8个赞
从代码的角度来看,您使用它很好:) 问题在于假设源材料是按 Zipf 排序的,而它显然是按字母顺序排列的。使用的全部意义ZipfDistribution
在于,words[0] 必须是最常见的单词(提示:它是“the”),并且大约是words[1] 频率的两倍)等。
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