I have say a

1) n cross n matrix A

2)  n cross 1 matrix B

I want to elementwise divide that is /~ each column of  by B and store in A itself like this 

If b_1 is in B and a_11 is in A i want   b_1/~a_11 in a_11

That is i divide

B /~ A first column

B /~ A second column

Like that for all its n columns

Kind help please

I have give this below fit command my data is only continous data either positive or negative float data. Their never any complex number at all.

I use the below fit command

Error, complex argument to max/min

It can be observed it is running into error in C1 I dont know why can someone suggest where should I check and why is this happening kind help.   In Excel we can see the intercept coming big.

I attach the toycode to see the error I get too

toycode.mw

I have been try to code the 

mdl:-Fit(x, y, opts)
command in Deep learning package

But i feel new to that command I am making errors 

Can I get a small toy code how to call it and its output on train and test

so that i could learn

kind help please

Say I have 20 userdefined functions defined by me say

Now i required function which picks one of the userdefined from the above 20 functions randomly

1) Say I have an Excel sheet with first column with my dependent variable values Y

2) Remaining columns to the left say some maximum 30 columns are independent variable

One thing is to import the excel columns to maple matrix

Then matrix will have first column dependent variable

Another's independent variables

3) Now i need to pick 2 independent variables columns and ( the dependent variable columns say Y which is the first column)

4) apply the normal regular MLR regression on it  then check if R^2 is good the p vaule are below 0.05

5) I print the column names of those columns

The first row will be the header column which has the variable name.

Kind help someone please kind help your help will be great greatly acknowledged