Spam or Ham Text Classification using Logistic Regression

Individual and business clients like to utilize wellsprings of correspondence. The use and significance of messages ceaselessly develop regardless of the predominance of elective methods, like electronic messages, versatile applications, and informal organizations. As the volume of business-basic me...

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Bibliographic Details
Published in:Turkish journal of computer and mathematics education 2021-01, Vol.12 (9), p.426-433
Main Authors: Rao, G Siva Nageswara, Madhuri, P, Sudheer, D, Meghana, D
Format: Article
Language:English
Subjects:
Assaults
Classification
Clients
Electronic mail
Malware
Messages
Phishing
Spamming
Online Access:Get full text
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Summary:Individual and business clients like to utilize wellsprings of correspondence. The use and significance of messages ceaselessly develop regardless of the predominance of elective methods, like electronic messages, versatile applications, and informal organizations. As the volume of business-basic messages keeps on developing, the need to robotize the administration of messages increments for a few reasons, for example, spam email order, phishing email characterization, and multi-envelope classification, among others. Sending a gigantic number of undesirable sends makes security danger clients. These are sent along informing frameworks as substance. Mobile telephones in a real sense are being made un-operational through these sorts of digital assaults. This undertaking means to fabricate an AI model that figures out how to distinguish the assaulting through malware caused inside informing that contains various types of sources that incorporate content, video and sound. The model intends to get familiar with the assaulting caused through malware and afterwards trigger an activity that counters the assault dependent on its sort· Keywords:
ISSN:1309-4653