What kind of algorithm would you use to distinguish between a spam email vs a non spam one?

Heuristic or Rule-Based Spam Filtering Technique Algorithms use pre-defined rules in the form of a regular expression to give a score to the messages present in the e-mails. Based on the scores generated, they segregate emails into spam non-spam categories.

What is ML spamming?

Spamming, in the context of video games, refers to the repeated use of the same item or action. For example, “grenade spamming” is the act of a player throwing lot of grenades in succession into an area.

What is the algorithm used for spam email classification?

Some of the most popular spam email classification algorithms are Multilayer Perceptron Neural Networks (MLPNNs) and Radial Base Function Neural Networks (RBFNN). Researchers used MLPNN as a classifier for spam filtering but not many of them used RBFNN for classification.

How do email servers detect spam?

An email server detects spam by using spam filter software which evaluates incoming emails on a number of criteria. (Yes, you can run an email server without having spam filter software enabled – you’d just see any and all spam email.)

What type of machine learning algorithm do we need to detect malicious emails?

Different machine learning algorithms can detect spam, but one that has gained appeal is the “naïve Bayes” algorithm. As the name implies, naïve Bayes is based on “Bayes’ theorem,” which describes the probability of an event based on prior knowledge.

What is spam filtering in machine learning?

• Previous Likeness Based Spam Filtering Technique: This approach uses memory-based, or instance-based, machine learning methods to classify incoming emails based to their resemblance to stored examples (e.g. training emails).

Is there any machine learning method for email spam detection?

There is some related work that apply machine learning methods in email spam detection, A. Karim, S. Azam, B. Shanmugam, K. Kannoorpatti and M. Alazab. They describe a focused literature survey of Artificial Intelligence Revised (AI) and Machine learning methods for email spam detection.

What is the best algorithm for spam detection?

Spam detection is a classification problem. Naive Bayes is the easiest classification algorithm (fast to build, regularly used for spam detection). So I will suggest that you start with it.

Is naive Bayes the best algorithm for spam detection?

Automatic email filtering may be the most effective method of detecting spam but nowadays spammers can easily bypass all these spam filtering applications easily. Naive Bayes is one of the utmost well-known algorithms applied in these procedures.

What is the accuracy of your email detection algorithm?

If our algorithm predicts all the email as non-spam, it will achieve an accuracy of 80\%. And for some problem that has only 1\% of positive data, predicting all the sample as negative will give them an accuracy of 99\% but we all know this kind of model is useless in a real life scenario.