In an interview, I was asked the intuition behind the weight vector. I told the weight vector is a vector which we try to minimize to a local minima with the help of regulariser so we don't overfit. Weights tells us the influence of a feature on the model.
Although I am not sure if my intuition is correct. Is Weight vector W always normal to the plane? Say we have 5 features and after training say logistic reg we get weight vector of 5 values. Does this mean i have 5 W's each with its own plane? Because W is always normal to the plane π.
First I was asked when we say that there is a plane π, and the normal to the plane π is W. What does it mean? Later I was asked what can we interpret from weight vector? Is Weight vector W same as W which is normal to the plane
It would really help if someone could help me clear this understanding visually and intuitively.
