Machine Learning Techniques Used for Spam Filtering

computer engineering

Electronic mail has become the most widely used method of communication in the current day. It is also the quickest and most cost-effective method of communication. A significant number of residents have made the process of data sharing a routine component of their day-to-day life with the passage of time. Email is susceptible to a huge number of possible dangers because of the ease with which it can be used by those who utilize it. One of the most fundamental dangers that are involved with internet communication is the sending of unsolicited commercial email, which is sometimes referred to as spam. The proliferation of the spam movement is a problem that ought to be of concern since it wastes the capacity of the system to transport data, the time of consumers, and the space in memory, and it also results in monetary loss for both customers and enterprises. As a result of this investigation, we propose a model that is capable of performing characteristic choice for the purpose of ruthless spam recognition among email messages. Our intention is to simplify the grouping parameter, the figure precision, and the computation time in order to better prepare for the characterization calculations that will follow.

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