Building a logistic regression classifier

Despite the word regression being present in the name, logistic regression is actually used for classification purposes. Given a set of datapoints, our goal is to build a model that can draw linear boundaries between our classes. It extracts these boundaries by solving a set of equations derived from the training data.

How to do it…

  1. Let's see how to do this in Python. We will use the file that is provided to you as a reference. Assuming that you imported the necessary packages, let's create some sample data along with training labels:
    import numpy as np from sklearn import linear_model import matplotlib.pyplot as plt X = np.array([[4, 7], [3.5, 8], [3.1, 6.2], [0.5, 1], [1, 2], [1.2, ...

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