PCA 4 DCA: The Application of Principal Component Analysis to the Dendritic Cell Algorithm

Uwe Aickelin,Robert Oates,Julie Greensmith,Feng Gu

doi:10.2139/ssrn.2830357

Uwe Aickelin, Robert Oates + Show 2 more

Open Access

https://doi.org/10.2139/ssrn.2830357

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Abstract

As one of the newest members in the field of artificial immune systems (AIS), the Dendritic Cell Algorithm (DCA) is based on behavioural models of natural dendritic cells (DCs). Unlike other AIS, the DCA does not rely on training data, instead domain or expert knowledge is required to predetermine the mapping between input signals from a particular instance to the three categories used by the DCA. This data preprocessing phase has received the criticism of having manually over-fitted the data to the algorithm, which is undesirable. Therefore, in this paper we have attempted to ascertain if it is possible to use principal component analysis (PCA) techniques to automatically categorise input data while still generating useful and accurate classification results. The integrated system is tested with a biometrics dataset for the stress recognition of automobile drivers. The experimental results have shown the application of PCA to the DCA for the purpose of automated data preprocessing is successful.

Highlights

The Dendritic Cell Algorithm (DCA) is an emerging algorithm within the field of artificial immune systems (AIS) [3]
As the Kα values produced by the DCA share the same time series with the original dataset, the whole duration is divided into the same segments as suggested above
We have shown that it is possible to integrate principal component analysis (PCA) with the DCA for the purpose of automated data preprocessing

Summary

Introduction

The Dendritic Cell Algorithm (DCA) is an emerging algorithm within the field of artificial immune systems (AIS) [3]. It is a biologically inspired population based algorithm which is derived from behavioural models of natural dendritic cells (DCs) [13]. It is underpinned by a recent paradigm in immunology termed the danger theory [14], which states that the human immune system is activated in response to the detection of ‘danger signals’. For further details about the nature of the individual signal values, refer to Greensmith et al [6]

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