主要内容

removeEmptyDocuments

从令牌化的文档阵列，词袋模型或n-grams型号中删除空文档

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Syntax

newDocuments = removeEmptyDocuments(documents)
newBag = removeEmptyDocuments(bag)
[___，idx] = emoveementyDocuments（___)

Description

example

newDocuments= removeEmptyDocuments(documents)removes documents which have no words fromdocuments.

example

newBag= removeEmptyDocuments(袋)removes documents which have no words or n-grams from the bag-of-words or bag-of-n-grams model袋.

example

[___,idx] = removeEmptyDocuments(___)also returns the indices of the removed documents.

Examples

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打开实时脚本

Remove documents containing no words from an array of tokenized documents.

Create an array of tokenized documents which includes empty documents.

documents = tokenizedDocument(["an example of a short sentence""""a second short sentence"""])
documents = 4x1 tokenizedDocument: 6 tokens: an example of a short sentence 0 tokens: 4 tokens: a second short sentence 0 tokens:

Remove the empty documents.

newDocuments = removeEmptyDocuments(documents)
newDocuments = 2x1 tokenizedDocument: 6 tokens: an example of a short sentence 4 tokens: a second short sentence
打开实时脚本

Remove documents containing no words from bag-of-words model.

从一系列令牌化文档中创建一个单词型模型。

documents = tokenizedDocument(["An example of a short sentence.""""A second short sentence."""]); bag = bagOfWords(documents)
袋= bagOfWords with properties: Counts: [4x9 double] Vocabulary: ["An" "example" "of" "a" "short" ... ] NumWords: 9 NumDocuments: 4

Remove the empty documents from the bag-of-words model.

newBag = removeEmptyDocuments(bag)
newBag = bagOfWords with properties: Counts: [2x9 double] Vocabulary: ["An" "example" "of" "a" "short" ... ] NumWords: 9 NumDocuments: 2
打开实时脚本

删除包含数组中不包含单词的文档，并使用删除文档的索引也删除相应的标签。

Create an array of tokenized documents which includes empty documents.

documents = tokenizedDocument(["an example of a short sentence""""a second short sentence"""])
documents = 4x1 tokenizedDocument: 6 tokens: an example of a short sentence 0 tokens: 4 tokens: a second short sentence 0 tokens:

Create a vector of labels.

labels = [“ T”;"F";"F";“ T”]
labels =4x1 string“ t”“ f”“ f”“ t”

Remove the empty documents and get the indices of the removed documents.

[newDocuments, idx] = removeEmptyDocuments(documents)
newDocuments = 2x1 tokenizedDocument: 6 tokens: an example of a short sentence 4 tokens: a second short sentence
idx =2×12 4

Remove the corresponding labels fromlabels.

标签（idx）= []
labels =2x1 string“ t”“ f”

Input Arguments

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Input documents, specified as a象征性文档大批.

Input bag-of-words or bag-of-n-grams model, specified as a袋OfWords对象或一个袋OfNgrams目的。

Output Arguments

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Output documents, returned as a象征性文档大批.

Output model, returned as a袋OfWords对象或一个袋OfNgrams目的。The type ofnewBagis the same as the type of袋.

Indices of removed documents, returned as a vector of positive integers.

See Also

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