# SklearnProjector **`class SklearnProjector(config)`** Bases: [`Projector`](squirro.lib.nlp.steps.projectors.Projector.md#squirro.lib.nlp.steps.projectors.Projector) The generic scikit-learn [`Projector`](squirro.lib.nlp.steps.projectors.Projector.md#squirro.lib.nlp.steps.projectors.Projector) step projects from one vector space to another. For more info see [Decomposition](https://scikit-learn.org/stable/modules/classes.html#module-sklearn.decomposition). **Note** - So far only svd is supported -> [TruncatedSVD](https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.TruncatedSVD.html#sklearn.decomposition.TruncatedSVD) **Input** - all input fields need to be of type [`list`](https://docs.python.org/3.11/library/stdtypes.html#list) [ [`float`](https://docs.python.org/3.11/library/functions.html#float) or [`int`](https://docs.python.org/3.11/library/functions.html#int) ] or `numpy.ndarray` **Output** - all output fields are filled with data of type `numpy.ndarray` with shape (‘n_components’,) Parameters - `type` ([`str`](https://docs.python.org/3.11/library/stdtypes.html#str)) – sklearn - `model_type` ([`str`](https://docs.python.org/3.11/library/stdtypes.html#str)`, ``'svd'`) – Type of scikit-learn projection - `model_kwargs` ([`dict`](https://docs.python.org/3.11/library/stdtypes.html#dict)`, ``{}`) – Keyword arguments for the scikit-learn model - `n_components` ([`int`](https://docs.python.org/3.11/library/functions.html#int)) – Number of vector components after projection - `normalize_output` ([`bool`](https://docs.python.org/3.11/library/functions.html#bool)`, ``True`) – Whether or not to normalize the output **Example** ```json { "step": "projector", "type": "sklearn", "model_type": "svd", "n_components": 100, "input_field": "embedded_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))