Wait, how is K-NN harder to implement than a perception... Even in hardware? What about linear regression? What about decision trees? What about naive Bayes?
A single layer perceptron IS linear regression + some non-linearity of the output. I think in reality they could have used the word "logistic regression" but chose perceptron because it sounds better.
Performing nearest neighbors search is much more expensive than a simple multiply-add. I don’t know about the other, my idea is that a perceptron is much easier to implement in hardware/low-level operations.
