- #1
themagiciant95
- 57
- 5
In a scientific paper (Neural Networks: A Systematic Introduction, page 86) about the Perceptron Algorithm I found:
A good initial heuristic is to start with the average of the positive input vectors minus the average of the negative input vectors. In many cases this yields an initial vector near the solution region.
Can you show me geometrically why this is true?
A good initial heuristic is to start with the average of the positive input vectors minus the average of the negative input vectors. In many cases this yields an initial vector near the solution region.
Can you show me geometrically why this is true?