Can I do regression with deep learning?

Question

I am new to ML, and I have a dataset:

Where:

X = {X_1, X_2, X_3, X_4, X_5, X_6, X_7};
Y = Y;

I'm trying to find the possible relationship between X and Y like Y = M(X) using Deep Learning. To my knowledge, this is a regression task since the data type of my target Y is real.

I have tried some regression algorithms like LMS and Stepwise regression but none of those gives me a promising result. So I'm turning into the deep neural network solution, so:

• Can ANN do this regression task?
• How to design the network, especially the type of layers, activation function, etc.?
• Is there some existing NN architecture I can refer to?

Any help is appreciated.

Answer 1

I don't have a solution for the machine learning part, but I do have a solution that would maybe work (since you asked for any other solutions).

I will say it might be difficult to use machine learning, since not only do you need to find a relationship (assuming there is one), but you need to find the right type of model (is it linear, quadratic, exponential, sinusoidal, etc.) and then you need to find the parameters for those models.

In the R programming language, it is easy to set up a multiple linear regression, for example. Here is a sketch of the R code you would use to find a linear regression.

data = load("data.Rdata") # or load a table or something
regression = lm(Y ~ X1 + X2 + X3 + X4 + X5 + X6 + x7, data = data)
print(summary(regression))

Edit: you might get better answers here: https://datascience.stackexchange.com/