Negative Selection Algorithm
On this page, you will find a collection of practical examples that demonstrate how to use the negative selection classes implemented in our package.
BNSA (Binary Negative Selection Algorithm)
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In the example present in this notebook 1000 random samples were generated, arranged in two groups, one for each class.
It uses the mushrooms database, which contains information about edible and poisonous mushrooms.
RNSA (Real-Valued Negative Selection Algorithm)
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In the example present in this notebook 500 random samples were generated, arranged in two groups, one for each class, we can see the non-self detectors generated below
Example using the NSA iris database, which contains four-dimensional samples and three output classes (Setosa, Versicolor and Virginica).
To classify geyser eruptions in Yellowstone National Park, this notebook uses the Old Faithful database.