Weight by Term Frequency - Inverse Document Frequency
Weight a term-document matrix by term frequency - inverse document frequency.
weightTfIdf(m, normalize = TRUE)
m |
A |
normalize |
A Boolean value indicating whether the term frequencies should be normalized. |
Formally this function is of class WeightingFunction with the
additional attributes name and acronym.
Term frequency \mathit{tf}_{i,j} counts the number of occurrences n_{i,j} of a term t_i in a document d_j. In the case of normalization, the term frequency \mathit{tf}_{i,j} is divided by ∑_k n_{k,j}.
Inverse document frequency for a term t_i is defined as
\mathit{idf}_i = \log_2 \frac{|D|}{|\{d \mid t_i \in d\}|}
where |D| denotes the total number of documents and where |\{d \mid t_i \in d\}| is the number of documents where the term t_i appears.
Term frequency - inverse document frequency is now defined as \mathit{tf}_{i,j} \cdot \mathit{idf}_i.
The weighted matrix.
Gerard Salton and Christopher Buckley (1988). Term-weighting approaches in automatic text retrieval. Information Processing and Management, 24/5, 513–523.
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