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A Negative Selection Algorithm Based on Email Classification Techniques

Keywords: Negative selection , E-mail Classification , Algorithm , Self , Non-Self , Artificial Immune System , Classification accuracy.

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Abstract:

Aiming to develop an immune based system, the negative selection algorithm aid in solving complex problems in spam detection. This is been achieve by distinguishing spam from non-spam (self from non-self). In this paper, we propose an optimized technique for e-mail classification. This is done by distinguishing the characteristics of self and non-self that is been acquired from trained data set. These extracted features of self and non-self are then combined to make a single detector, therefore reducing the false rate. (Non-self that were wrongly classified as self). The result that will be acquired in this paper will demonstrate the effectiveness of this technique in decreasing false rate.

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