Naive Bayes algorithm was invented by Thomas Bayes and introduced in 1730s. Thomas Bayes didn’t live a very long life and his work was rigorously studied, curated, structured, corrected and even published by his friend Richard Price.
“An Essay towards solving a Problem in the Doctrine of Chances” was published in 1763 by Price on behalf of Thomas Bayes which was the first publication including Bayes Theorem.
More than two centuries since its discovery, Bayes Theorem inspired and influenced many discussions, algorithms, research and technology in statistics field and pioneered probabilistic statistics.
Thomas Bayes only published two papers when he was alive and a third paper introducing Bayes Theorem was edited and published by his friend Richard Price. You can see the dates and titles of these three papers below:
Thomas Bayes – Divine Benevolence, or an Attempt to Prove That the Principal End of the Divine Providence and Government is the Happiness of His Creatures : 1731
Thomas Bayes – An Introduction to the Doctrine of Fluxions, and a Defence of the Mathematicians Against the Objections of the Author of The Analyst : 1736
Richard Price – An Essay towards solving a Problem in the Doctrine of Chances : 1763 : read here
Thomas Bayes, an English mathematician and theologian, developed the foundation of what is now known as Bayesian probability theory. Unfortunately, there is limited information available about the specific inspiration behind Bayes’ work, as he did not publish his ideas during his lifetime. His influential paper, “An Essay towards solving a Problem in the Doctrine of Chances,” was published posthumously in 1763 by his friend Richard Price.
The inspiration for Bayes’ theorem likely came from his interest in the philosophy of probability and his desire to understand how to update beliefs in the face of new evidence. Bayes was influenced by earlier works in probability theory, including the works of Thomas Simpson and Pierre-Simon Laplace.
It is important to note that while Bayes’ theorem is attributed to Thomas Bayes, the formulation and development of the theorem might have involved contributions from others, including Richard Price, who edited and published Bayes’ work after his death.
Overall, the exact inspirations that led to Thomas Bayes’ formulation of Bayesian theorem are not well-documented. However, we can make pretty sophisticated speculations that his work was influenced by earlier ideas in probability theory and his interest in updating beliefs based on new evidence. This is a particularly interesting point considering it lines up with his progressive theological views and active position in the Protestant church.
Bayes’ theorem played a crucial role in the development of modern statistics by introducing a formal framework for updating beliefs and making inferences based on probabilistic reasoning. Here’s how Bayes’ theorem contributed to the field of modern statistics:
In conclusion, Bayes’ theorem laid the groundwork for modern statistics by introducing the concepts of prior and posterior distributions, enabling the quantification of uncertainty, providing a foundation for decision theory, accommodating complex models and data, and benefiting from computational advancements. The Bayesian framework continues to be a vibrant area of research and application in statistics, offering a powerful and flexible approach to modeling and inference.
In this brief article we have covered the history of Naive Bayes Theorem which Naive Bayes Machine Learning algorithm is based on.