I have sought some help and trained a regression model that takes in a single dependent variable Y and gives the three independent variable R, B and G as output. This has been done in attempt to approximate a function : Y = R+B+G.
The neural network responsible for this is:-
input1 = Input(shape=(1,)) l1 = Dense(10, activation='relu')(input1) l2 = Dense(50, activation='relu')(l1) l3 = Dense(50, activation='relu')(l2) out = Dense(3)(l3)
But, this is done using Keras and tensorflow. As this model ran successfully, I now need to implement the same model (function approximation using regression). The problem can be solved using neural networks(as shown above) but there is no mathematical method of duplicating the solution without using any high level API.
How is the above neural network able to do this?
P.S: I need to understand the mathematics and logic behind the implementation.