Weight a term-document matrix by term frequency - inverse document frequency.
weightTfIdf(m, normalize = TRUE)A TermDocumentMatrix in term frequency format.
A Boolean value indicating whether the term frequencies should be normalized.
The weighted matrix.
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 \(\sum_k n_{k,j}\).
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 \(\mathit{tf}_{i,j} \cdot \mathit{idf}_i\).
Gerard Salton and Christopher Buckley (1988). Term-weighting approaches in automatic text retrieval. Information Processing and Management, 24/5, 513--523.