Regularization, Machine Learning, Convex Optimization, Lagrangian, Ml So Good.
Imagine if threshold is 1 and our P(W) is 1.001, still we would see a huge loss, which is not good, to make things a bit smoother we make a linear dependency between P(W) and a new term lambda. Smoother P(W) with lambda term wrt W Our new equation after this became, general regularization Does it