Classification Accuracy

Binary classification metrics with logistic regression and near-default options

Now we proceed to fit an example model to illustrate binary classification metrics. We will continue to use logistic regression with near-default options. The following code loads the model class and creates a model object.

from sklearn.linear_model import LogisticRegression 

example_lr = LogisticRegression(C=0.1, class_weight=None, 
                                dual=False, fit_intercept=True,
                                intercept_scaling=1, max_iter=100, 
                                multi_class='auto', n_jobs=None, 
                                penalty='l2', random_state=None, 
                                solver='liblinear', tol=0.0001,