Comparison Of Classifier Outputs Using AIS And Non-AIS Based Data Mining Algorithms

Rama Krushna Das, Manisha Panda, Sanghamitra Dash

Abstract


The immune system is a remarkable information processing and self-learning system that inspires artificial immune system (AIS). Classification is a gradual practice for allocating a given piece of input into any of the known category also is an important machine learning technique. This paper describes analysis and comparison of different datasets using different AIS based classification algorithms using WEKA. A comparison of different datasets through the different AIS and non-AIS based algorithm is used to select the best suitable algorithm for the corresponding dataset. Apart from that some other related factors are compared for describing and evaluating the best classifier.


Keywords


Accuracy; Antibody; Artificial Immune System; classification; classifier; CLONALG; CSCA; cloning; intrusion detection; machine learning

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