Naive bayes: Some of these include

Some of these include: Gaussian Naïve Bayes (GaussianNB): This is a variant of the Naïve Bayes classifier, which is used with Gaussian distributions—i.e. normal distributions—and continuous variables. This model is fitted by finding the mean and standard deviation of each class. Naive Bayes is a machine learning classification algorithm that predicts the category of a data point using probability. It assumes that all features are independent of each other. Learn about naive Bayes classifiers, a family of probabilistic models that assume feature independence given the class. Find out how they work, how to train them, and how they compare with other methods. What Is the Naive Bayes Classifier Algorithm? The Naive Bayes classifier algorithm is a machine learning technique used for classification tasks. It is based on Bayes’ theorem and assumes that features are conditionally independent of each other given the class label. The algorithm calculates the probability of a data point belonging to each class and assigns it to the class with the highest probability. Naive Bayes is known for its simplicity, efficiency, and effectiveness in handling ...