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Improving spam filtering by combining naive bayes with simple k-nearest neighbor searches (2008).
| Content Provider | CiteSeerX |
|---|---|
| Author | Etzold, Daniel |
| Abstract | Using naive Bayes for email classification has become very popular within the last few months. They are quite easy to implement and very efficient. In this paper we want to present empirical results of email classification using a combination of naive Bayes and k-nearest neighbor searches. Using this technique we show that the accuracy of a Bayes filter can be improved slightly for a high number of features and significantly for a small number of features. |
| File Format | |
| Publisher Date | 2008-01-01 |
| Access Restriction | Open |
| Subject Keyword | Naive Bayes Spam Filtering Simple K-nearest Neighbor Search Email Classification Last Month Bayes Filter High Number K-nearest Neighbor Search Empirical Result Small Number |
| Content Type | Text |
| Resource Type | Article |