A SURVEY: SPAM FILTERING USING MACHINE LEARNING ALGORITHMS
Journal Title: International Journal of Engineering Sciences & Research Technology - Year 2015, Vol 4, Issue 12
Abstract
In this paper, we show an exhaustive survey of late improvements in the utilization of machine learning algorithms to Spam filtering, concentrating on both textual-and image-based approaches. Rather than considering Spam filtering as a standard classification issue, we highlight the significance of considering particular attributes of the issue, particularly idea float, in outlining new filters. Two especially vital viewpoints not generally perceived in the writing are talked about: the troubles in overhauling a classifier taking into account the sack of-words representation and a noteworthy contrast between two early credulous Bayes models. By and large, we presume that while vital headways have been made in the most recent years, a few perspectives stay to be investigated, particularly under more reasonable assessment settings.
Authors and Affiliations
Deepak Kumar Agarwal*
Keywords
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