evalml.pipelines.LogisticRegressionPipeline.fit

LogisticRegressionPipeline.fit(X, y, objective_fit_size=0.2)

Build a model

Parameters

• X (pd.DataFrame or np.array) – the input training data of shape [n_samples, n_features]

• y (pd.Series) – the target training labels of length [n_samples]

• feature_types (list, optional) – list of feature types. either numeric of categorical. categorical features will automatically be encoded

Returns

self