# BowEmbedder **`class BowEmbedder(config)`** Bases: [`Embedder`](squirro.lib.nlp.steps.embedders.Embedder.md#squirro.lib.nlp.steps.embedders.Embedder) The bag of words [`Embedder`](squirro.lib.nlp.steps.embedders.Embedder.md#squirro.lib.nlp.steps.embedders.Embedder) encodes provided text based on gensim [doc2bow](https://radimrehurek.com/gensim/corpora/dictionary.html#gensim.corpora.dictionary.Dictionary.doc2bow). **Intput** - the input field needs to be of type [`list`](https://docs.python.org/3.11/library/stdtypes.html#list) [ [`str`](https://docs.python.org/3.11/library/stdtypes.html#str) ] **Output** - the output field is filled with data of type `numpy.ndarray` Parameters - `type` ([`str`](https://docs.python.org/3.11/library/stdtypes.html#str)) – bow - `min_doc_frequency` ([`int`](https://docs.python.org/3.11/library/functions.html#int)`, ``2`) – Minimum number of documents a term must appear in - `max_doc_fraction` ([`float`](https://docs.python.org/3.11/library/functions.html#float)`, ``0.75`) – Maximum fraction of documents a term can appear in - `max_n_words` ([`int`](https://docs.python.org/3.11/library/functions.html#int)`, ``None`) – Maximum dictionary size **Example** ```json { "step": "embedder", "type": "bow", "input_field": "text", "output_field": "embedded_text" } ``` Methods SummaryMethods Documentation **`load()`** Load a step **`process_batch(batch)`** Process a batch of documents. If not defined will default to using self.process_doc for each document in the batch. Parameters `batch` ([`list`](https://docs.python.org/3.11/library/stdtypes.html#list)`(`[`Document`](../technical/libnlp/base.md#squirro.lib.nlp.document.Document)`)`) – List of documents Returns List of processed documents Return type [list](https://docs.python.org/3.11/library/stdtypes.html#list)([Document](../technical/libnlp/base.md#squirro.lib.nlp.document.Document)) **`save()`** Save a step **`train(docs)`** Train on a step of a set of documents Parameters `docs` (`generator``(`[`Document`](../technical/libnlp/base.md#squirro.lib.nlp.document.Document)`)`) – Generator of documents Returns Generator of processed documents Return type generator([Document](../technical/libnlp/base.md#squirro.lib.nlp.document.Document))