nlpatl.models.classification.sklearn_classification

sci-kit learn classification wrapper

class nlpatl.models.classification.sklearn_classification.SkLearnClassification(model_name='logistic_regression', model_config={}, name='sklearn_classification')[source]

Bases: nlpatl.models.classification.classification.Classification

A wrapper of sci-kit learn classification class.

Parameters

model_name (str) – sci-kit learn classification model name. Possible values are logistic_regression, svc, linear_svc and random_forest.
model_config (dict) – Model paramateters. Refer to https://scikit-learn.org/stable/modules/classes.html#module-sklearn.linear_model
name (str) – Name of this classification

>>> import nlpatl.models.classification as nmcla
>>> model = nmcla.SkLearnClassification()

predict_proba(x, predict_config={})[source]

Parameters

x (np.ndarray) – Raw features
predict_config (dict) – Model prediction paramateters. Refer to https://scikit-learn.org/stable/modules/classes.html#module-sklearn.linear_model

Returns

Feature and probabilities

Return type

nlptatl.dataset.Dataset

train(x, y)[source]

Parameters

x (np.ndarray) – Raw features
y (list of string, int or float or np.ndarray.) – Label of data inputs