The third classifier we will cover is the
MaxentClassifier class, also known as a conditional exponential classifier or
logistic regression classifier. The maximum entropy classifier converts labeled feature sets to vectors using encoding. This encoded vector is then used to calculate weights for each feature that can then be combined to determine the most likely label for a feature set. For more details on the math behind this, see https://en.wikipedia.org/wiki/Maximum_entropy_classifier.
MaxentClassifier class requires the
NumPy package. This is because the feature encodings use
NumPy arrays. You can find installation details at the following link: