[source] # TF-IDF Transformer *Term Frequency - Inverse Document Frequency* is a measurement of how important a word is to a document. The TF-IDF value increases proportionally (linearly) with the number of times a word appears in a document (*TF*) and is offset by the frequency of the word in the corpus (*IDF*). !!! note TF-IDF Transformer assumes that its inputs are token frequency vectors such as those created by [Word Count Vectorizer](word-count-vectorizer.md). **Interfaces:** [Transformer](api.md#transformer), [Stateful](api.md#stateful), [Elastic](api.md#elastic), [Persistable](../persistable.md) **Data Type Compatibility:** Continuous only ## Parameters | # | Name | Default | Type | Description | |---|---|---|---|---| | 1 | smoothing | 1.0 | float | The amount of additive (Laplace) smoothing to add to the inverse document frequencies (IDFs). | ## Example ```php use Rubix\ML\Transformers\TfIdfTransformer; $transformer = new TfIdfTransformer(1.0); ``` ## Additional Methods Return the document frequencies calculated during fitting: ```php public dfs() : ?array ``` ## References [^1]: S. Robertson. (2003). Understanding Inverse Document Frequency: On theoretical arguments for IDF.