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Naïve Bayes algorithm is a supervised learning algorithm, which is based on Bayes theorem and used for solving classification problems. It is mainly used in text classification that includes a high-dimensional training dataset.
Mar 1, 2024 · A Naive Bayes classifiers, a family of algorithms based on Bayes’ Theorem. Despite the “naive” assumption of feature independence, these classifiers are widely utilized for their simplicity and efficiency in machine learning.
Nov 4, 2018 · Naive Bayes is a probabilistic machine learning algorithm that can be used in a wide variety of classification tasks. Typical applications include filtering spam, classifying documents, sentiment prediction etc. It is based on the works of Rev. Thomas Bayes (1702) and hence the name.
Jan 16, 2021 · The naive Bayes algorithm is a powerful and widely-used machine learning algorithm that is particularly useful for classification tasks. This article explains the basic math behind the Naive Bayes algorithm and how it works for binary classification problems.
May 23, 2024 · What is the Naive Bayes Algorithm? It is a classification technique based on Bayes’ Theorem with an independence assumption among predictors. In simple terms, a Naive Bayes classifier assumes that the presence of a particular feature in a class is unrelated to the presence of any other feature.
May 3, 2024 · Naive Bayes is a simple but powerful method in machine learning used for guessing categories of things. Imagine sorting emails into spam or inbox. Naive Bayes looks at each word (like a clue) and predicts how likely it is to be spam based on past emails.
Aug 15, 2020 · In this post you discovered the Naive Bayes algorithm for classification. You learned about: The Bayes Theorem and how to calculate it in practice. Naive Bayes algorithm including representation, making predictions and learning the model. The adaptation of Naive Bayes for real-valued input data called Gaussian Naive Bayes.
This training algorithm is an instance of the more general expectation–maximization algorithm (EM): the prediction step inside the loop is the E-step of EM, while the re-training of naive Bayes is the M-step.
The Naïve Bayes classifier is a supervised machine learning algorithm that is used for classification tasks such as text classification. They use principles of probability to perform classification tasks.
Dec 22, 2023 · Naive Bayes is a powerful, efficient, probabilistic algorithm used primarily for classification tasks in data science. It’s based on Bayes’ Theorem, which relates the probability of an event to prior knowledge or conditions related to the event.
