I work on Dendritic Cell Algorithm (DCA) for classification of binary data, but I do not understand some of its parts:
I'm going to use DCA for detecting spam SMS. So, I generate signals from the output of two ML algorithms (for example Naive Bayes and SVM) with confidence for each SMS. After that, run DCA for select DC that migrate. (Training phase)
Well, now, how do I determine the type of new SMS? (Test phase) Suppose the new SMS is not like any previous one.
I need an implementation in Python, C++ or Java.
Jason Brownlee provides an example of the Dendritic Cell Algorithm implemented in the Ruby Programming Language. The problem is a contrived anomaly-detection problem with ordinal inputs x range [0,50), where values that divide by 10 with no remainder are considered anomalies. Probabilistic safe and danger signal functions are provided, suggesting danger signals correctly with P(danger)=0.70, and safe signals correctly with P(safe)=0.95. (http://www.cleveralgorithms.com/nature-inspired/immune/dca.html), But my previous ambiguity has not been resolved yet.
When he wants to test its implementation, it uses the same data as previously trained the system. This is a mistake when new data is entered.
Can anybody explain this situation for me?
Thanks
Dear Mohsen Rahmanian ,
Look the link, may be useful.
http://www.cleveralgorithms.com/nature-inspired/immune/dca.html
http://www.freepatentsonline.com/9438621.html
Regards, Shafagat
Dr. Shafagat Mahmudova,
Thanks for your attention.
I've already viewed both links already mentioned, but I have not yet fixed my problem.
Thanks again.
Hello Dr. Rashidinejad
Thank you,
This description is good, but it is not enough for me. I need a practical example.
can anyone share python implementation of
Dendritic Cell Algorithm for intrusion detection?
Hello Dr. Gulshan Kumar Ahuja
This code was my first attempt. Hope to be useful.
Thanks Mohsen Rahmanian,
It is very helpful for me to understand the concept.
Please suggest to modify it for KDD dataset for intrusion detection. Sample of KDD dataset is attached herewith.
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