How is Naive Bayes used in spam filtering?

How is Naive Bayes used in spam filtering?

Naive Bayes classifiers work by correlating the use of tokens (typically words, or sometimes other things), with spam and non-spam e-mails and then using Bayes’ theorem to calculate a probability that an email is or is not spam.

Can we use Naive Bayes for email spam detection?

Naive Bayes is a probabilistic algorithm based on the Bayes Theorem used for email spam filtering in data analytics. If you have an email account, we are sure that you have seen emails being categorised into different buckets and automatically being marked important, spam, promotions, etc.

Why is Naive Bayes good for spam classification?

A bit of theory Naive Bayes classification is a simple probability algorithm based on the fact, that all features of the model are independent. In the context of the spam filter, we suppose, that every word in the message is independent of all other words and we count them with the ignorance of the context.

What is the Naive Bayes assumption?

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. For example, a fruit may be considered to be an apple if it is red, round, and about 3 inches in diameter.

Where are spam filters located?

A gateway spam filter typically sits behind the firewall of a network, looking for any email threats that are coming in to the network. Typically gateway filters will be physical hardware located on-premise in servers rather than being stored in the cloud.

What is naive in Naive Bayes?

Naive Bayes (NB) is ‘naive’ because it makes the assumption that features of a measurement are independent of each other. This is naive because it is (almost) never true.

How accurate is the naive Bayes spam filter in GitHub?

GitHub – ivedants/Naive-Bayes-Spam-Email-Classifier: An implementation of an email spam filter using Naive Bayes method. Observed accuracy: 96.98% This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. … Failed to load latest commit information.

What is naive Bayes classifier in email automation?

Automated filtering of emails takes place in this age and time of data analytics & machine learning through algorithms such as Naive Bayes Classifier, which apply the basic Bayes Theorem to the data. Before we get our hands dirty and analyses a real email dataset in Python, we will briefly learn about the Naive Bayes Algorithm in this article.

What is Bayesian spam filtering?

Most bayesian spam filtering algorithms are based on formulas that are strictly valid (from a probabilistic standpoint) only if the words present in the message are independent events.

What is naive Bayes algorithm in data analytics?

Naive Bayes Algorithm in data analytics forms the base for text filtering in Gmail, Yahoo Mail, Hotmail & all other platforms. Like Naive Bayes, other classifier algorithms like Support Vector Machine, or Neural Network also get the job done!