N1
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input
input
Nk
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input
input
Nk+1
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output
B
1
If two data clusters (classes) can be separated by a decision boundary in the form of a linear equation
they are called linearly separable.
Otherwise, i.e. if such a decision boundary does not exist, the two classes are called linearly inseparable. In this case, we cannot use a simple neural network.
For this purpose, we need neural networks with bias nodes, like the one in the following diagram.
The equation looks like this: