Hi,
In the lectures and exercices, it is said that if the data are centered and linearly separable, perceptron will always find a decision boundary without using bias.
However in this situation I don't understand how the perceptron will do :
Indeed the data seems centered to me and also linearly separable, but we can't find a decision boundary that works well without bias ... or am I wrong somewhere ?
Thanks in advance for the attention.