Naive Bayes is a classification algorithm which checks the probability of a test point belonging to a class. Unlike other algorithms, Naive Bayes is purely a classification algorithm. As explained in the last release this is the formula for the Bayes theorem and as the algorithm name suggests Naive Bayes is inspired by the Bayes…
In machine learning, classification is classifying data using certain input variables. A dataset with labels given (training dataset) is used to train the model in a way that the model can provide labels for datasets that are not yet labeled. Under classification, there are 2 types of classifiers: Binary Classification Multi-Class Classification Here let’s discuss…
Classification algorithms depend on the dataset being used, and data scientists have curated various algorithms that can be used in certain situations. Most popular types of Classification Algorithms: Linear Classifiers Logistic regression Naive Bayes classifier Support vector machines Kernel estimation k-nearest neighbor Decision trees Random forests Let’s discuss this in more detail and understand when…
