More on Naïve Bayes
Explore how to construct a quantum Naive Bayes classifier by integrating classical data pre-processing, quantum circuit computations, and post-processing. Understand the application of Bayes' Theorem in quantum machine learning and how to implement this hybrid algorithm for classification using simplified feature sets.
We'll cover the following...
Naïve Bayes is a probabilistic machine learning algorithm based on Bayes’ Theorem. Even though it’s simple, it has been successfully used in a wide variety of classification tasks.
We’ll tap the theoretical and practical knowledge we gathered in the last few chapters and use it to build a quantum Naïve Bayes classifier. Like the previous quantum classifier we introduced in the lesson Variational Hybrid Quantum Classical Algorithm, the quantum Naïve Bayes is a variational hybrid quantum-classical algorithm. It consists of three parts:
- We pre-process the data on a classical computer to determine the modifiers for a set of features.
We ...