org.apache.lucene.classification.document

## Class KNearestNeighborDocumentClassifier

- java.lang.Object
- - org.apache.lucene.classification.KNearestNeighborClassifier
  - - org.apache.lucene.classification.document.KNearestNeighborDocumentClassifier

- All Implemented Interfaces:
    Classifier<BytesRef>, DocumentClassifier<BytesRef>

      public class KNearestNeighborDocumentClassifier
      extends KNearestNeighborClassifier
      implements DocumentClassifier<BytesRef>

  A k-Nearest Neighbor Document classifier (see `http://en.wikipedia.org/wiki/K-nearest_neighbors`) based on `MoreLikeThis` .
  WARNING: This API is experimental and might change in incompatible ways in the next release.

- - ### Field Summary

    Fields
    Modifier and Type | Field and Description
    --- | ---
    `protected Map<String,Analyzer>` | `field2analyzer` map of per field analyzers

    - ### Fields inherited from class org.apache.lucene.classification.KNearestNeighborClassifier

      `classFieldName, indexSearcher, k, mlt, query, textFieldNames`

  - ### Constructor Summary

    Constructors
    Constructor and Description
    `KNearestNeighborDocumentClassifier(IndexReader indexReader, Similarity similarity, Query query, int k, int minDocsFreq, int minTermFreq, String classFieldName, Map<String,Analyzer> field2analyzer, String... textFieldNames)` Creates a `KNearestNeighborClassifier`.

  - ### Method Summary

    All Methods Instance Methods Concrete Methods
    Modifier and Type | Method and Description
    --- | ---
    `ClassificationResult<BytesRef>` | `assignClass(Document document)` Assign a class (with score) to the given `Document`
    `List<ClassificationResult<BytesRef>>` | `getClasses(Document document)` Get all the classes (sorted by score, descending) assigned to the given `Document`.
    `List<ClassificationResult<BytesRef>>` | `getClasses(Document document, int max)` Get the first `max` classes (sorted by score, descending) assigned to the given text String.

    - ### Methods inherited from class org.apache.lucene.classification.KNearestNeighborClassifier

      `assignClass, buildListFromTopDocs, getClasses, getClasses, toString`

    - ### Methods inherited from class java.lang.Object

      `clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait`

- - ### Field Detail

    - #### field2analyzer

          protected Map<String,Analyzer> field2analyzer

      map of per field analyzers

  - ### Constructor Detail

    - #### KNearestNeighborDocumentClassifier

          public KNearestNeighborDocumentClassifier(IndexReader indexReader,
                                                    Similarity similarity,
                                                    Query query,
                                                    int k,
                                                    int minDocsFreq,
                                                    int minTermFreq,
                                                    String classFieldName,
                                                    Map<String,Analyzer> field2analyzer,
                                                    String... textFieldNames)

      Creates a `KNearestNeighborClassifier`.
      Parameters:
        `indexReader` - the reader on the index to be used for classification
        `similarity` - the `Similarity` to be used by the underlying `IndexSearcher` or `null` (defaults to `ClassicSimilarity`)
        `query` - a `Query` to eventually filter the docs used for training the classifier, or `null` if all the indexed docs should be used
        `k` - the no. of docs to select in the MLT results to find the nearest neighbor
        `minDocsFreq` - `MoreLikeThis.minDocFreq` parameter
        `minTermFreq` - `MoreLikeThis.minTermFreq` parameter
        `classFieldName` - the name of the field used as the output for the classifier
        `field2analyzer` - map with key a field name and the related {org.apache.lucene.analysis.Analyzer}
        `textFieldNames` - the name of the fields used as the inputs for the classifier, they can contain boosting indication e.g. title^10

  - ### Method Detail

    - #### assignClass

          public ClassificationResult<BytesRef> assignClass(Document document)
                                                     throws IOException

      Assign a class (with score) to the given `Document`
      Specified by:
        `assignClass` in interface `DocumentClassifier<BytesRef>`
      Parameters:
        `document` - a `Document` to be classified. Fields are considered features for the classification.
      Returns:
        a `ClassificationResult` holding assigned class of type `T` and score
      Throws:
        `IOException` - If there is a low-level I/O error.

    - #### getClasses

          public List<ClassificationResult<BytesRef>> getClasses(Document document)
                                                          throws IOException

      Get all the classes (sorted by score, descending) assigned to the given `Document`.
      Specified by:
        `getClasses` in interface `DocumentClassifier<BytesRef>`
      Parameters:
        `document` - a `Document` to be classified. Fields are considered features for the classification.
      Returns:
        the whole list of `ClassificationResult`, the classes and scores. Returns `null` if the classifier can't make lists.
      Throws:
        `IOException` - If there is a low-level I/O error.

    - #### getClasses

          public List<ClassificationResult<BytesRef>> getClasses(Document document,
                                                                 int max)
                                                          throws IOException

      Get the first `max` classes (sorted by score, descending) assigned to the given text String.
      Specified by:
        `getClasses` in interface `DocumentClassifier<BytesRef>`
      Parameters:
        `document` - a `Document` to be classified. Fields are considered features for the classification.
        `max` - the number of return list elements
      Returns:
        the whole list of `ClassificationResult`, the classes and scores. Cut for "max" number of elements. Returns `null` if the classifier can't make lists.
      Throws:
        `IOException` - If there is a low-level I/O error.

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