Investigations into Effectiveness of Gaussian And Nearest Mean Classifiers for Spam Detection

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Provided by: Creative Commons
Topic: Security
Format: PDF
The Knowledge Discovery and Data mining (KDD) field draws on findings from statistics, databases, and artificial intelligence to construct tools that let users gain insight from massive data sets. This paper presents the results of investigations into the effectiveness of Gaussian and nearest mean classifiers for spam detection. The results are in the form of traces of probability of error and time taken for classification. Since spam is increasingly becoming difficult to detect, so these automated techniques will help in saving lot of time and resources required to handle email messages.
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