## Uses of Class
org.apache.nutch.scoring.similarity.util.LuceneAnalyzerUtil.StemFilterType

- Packages that use LuceneAnalyzerUtil.StemFilterType
  Package | Description
  --- | ---
  org.apache.nutch.scoring.similarity.util | Utility package for Lucene functions.

- - ### Uses of LuceneAnalyzerUtil.StemFilterType in org.apache.nutch.scoring.similarity.util

    Methods in org.apache.nutch.scoring.similarity.util that return LuceneAnalyzerUtil.StemFilterType
    Modifier and Type | Method | Description
    --- | --- | ---
    `static LuceneAnalyzerUtil.StemFilterType` | LuceneAnalyzerUtil.StemFilterType.`valueOf​(String name)` | Returns the enum constant of this type with the specified name.
    `static LuceneAnalyzerUtil.StemFilterType[]` | LuceneAnalyzerUtil.StemFilterType.`values()` | Returns an array containing the constants of this enum type, in the order they are declared.

    Constructors in org.apache.nutch.scoring.similarity.util with parameters of type LuceneAnalyzerUtil.StemFilterType
    Constructor | Description
    --- | ---
    `LuceneAnalyzerUtil​(LuceneAnalyzerUtil.StemFilterType stemFilterType, boolean useStopFilter)` | Creates an analyzer instance based on Lucene default stopword set if the param useStopFilter is set to true
    `LuceneAnalyzerUtil​(LuceneAnalyzerUtil.StemFilterType stemFilterType, List<String> stopWords, boolean addToDefault)` | Creates an analyzer instance based on user provided stop words.
    `LuceneTokenizer​(String content, LuceneTokenizer.TokenizerType tokenizer, boolean useStopFilter, LuceneAnalyzerUtil.StemFilterType stemFilterType)` | Creates a tokenizer based on param values
    `LuceneTokenizer​(String content, LuceneTokenizer.TokenizerType tokenizer, List<String> stopWords, boolean addToDefault, LuceneAnalyzerUtil.StemFilterType stemFilterType)` | Creates a tokenizer based on param values
    `LuceneTokenizer​(String content, LuceneTokenizer.TokenizerType tokenizer, LuceneAnalyzerUtil.StemFilterType stemFilterType, int mingram, int maxgram)` | Creates a tokenizer for the ngram model based on param values