Congrats, if you’ve thoroughly & understood this article, you’ve already taken you first step to master this algorithm. If the mail contains a large number of those keywords then there will be higher chances for it to be spam. In machine learning, Naive Bayes Classifier belongs to the category of Probabilistic Classifiers. How Naive Bayes classifier algorithm works in machine learning Click To Tweet. Basics of Machine Learning and a simple implementation ... ending with a simple implementation of the Naive Bayes ... Let’s move on to the practical implementation of the Naive Bayes algorithm. Naive Bayes Classifier Defined. Naive Bayes is a simple technique for constructing classifiers: models that assign class labels to problem instances, represented as vectors of feature values, where the class labels are drawn from some finite set. Bayes theorem named after Rev. From here, all you need is practice. Naive Bayes is a machine learning model that is used for large volumes of data, even if you are working with data that has millions of data records the recommended approach is Naive Bayes. Thomas Bayes. Naive Bayes algorithm can be used to filter the Spam mails. What is Bayes Theorem? It works on conditional probability. Naive Bayes classifiers are a collection of classification algorithms based on Bayes’ Theorem.It is not a single algorithm but a family of algorithms where all of them share a common principle, i.e. A probabilistic classifier can predict given observation by using a probability distribution over a… It is a fast and uncomplicated classification algorithm. The Naive Bayers classifier is a machine learning algorithm that is designed to classify and sort large amounts of data. So let’s first discuss the Bayes Theorem. every pair of features being classified is independent of each other. Introduction. It gives very good results when it comes to NLP tasks such as sentimental analysis. It is fine-tuned for big data sets that include thousands or millions of data points and cannot easily be processed by human beings. To understand the naive Bayes classifier we need to understand the Bayes theorem. A list of keywords(on which basis a mail is decided to be a spam or not) is made and then the mail is checked for those keywords. In this article, we looked at one of the supervised machine learning algorithm “Naive Bayes” mainly used for classification.