How to train a Neural Network with an input data set that comprises of numeric values as well as nominal variables (such as the base fluid used which could be either 'Water', 'Oil' or 'Slickwater')?

Hi, I am trying to model a production data set using neural network. I am using a static 2 -layer feedforward neural network for the same (10 neurons hidden layer, 1 neuron output, dividerand, trainlm, transfer function-logsigmoid for hidden and linear for output).

My input data set comprises of 125 production well. Each well has 9 variables, 6 of which are numeric whereas the rest 3 are nominal variable (like orientation of well which could be north, south, east or west....base fluid used, which could be either of water, oil or slickwater).

When I load this dataset into matlab for training of neural network. It shows error that the input data should either be 'numeric' or 'logical'.

So, firstly is there any way I could train my network simultaneously using a combination of numeric and nominal variables. Secondly, if not is there any way I could rationally code numerical variables into their corresponding numeric values.

Thanks for your help in advance.

[Greg Heath]

Well, what were you putting in? Example?

[Kushagra Kakar]

I imported the whole data set including non numeric nominal variables as a cell array and tried to train the network. But it gave error that the Input{7,1} should either be numeric or logical. When I checked in the data set the particular cell was assigned to string 'Water'. I hope it helps.

Answer 1

[Ahmed]

Try to code your nominal variables as dummy binary variables, then input that into your neural network.

nomvar = nominal(randi(3,10,1));
dumvar = dummyvar(nomvar),

[Kushagra Kakar]

Could you please elaborate a bit more on how would I use the 'dummyvar' to replace the nominal variables in the imported data set...and one more thing how should I import my data set, as a Matrix, Cell Array etc. ??

Thanks,KK

Answer 2

[Iain]

You could make your non-numeric values into numeric ones by using enumerations.

E.g.

 Oil = 1;
 Water = 2;
 Slickwater = 3;
 Thebloodoftheinnocent = 4;

 Fluid = Oil;

Also, you could replace the north/south etc, with compass headings. 0 = North, pi = south, etc.

[Greg Heath]

I assume slickwater is less viscous than water.

Then if Thebloodoftheinnocent is less viscous than slickwater, shouldn't the numbers 1 to 4 be reversed to 4 to 1?

[Kushagra Kakar]

Hi Lain, if I use these enumerations then I would imply that the difference in production due to water and oil (2-1) is same as the difference in production due to Slickwater and Water (3-2)....which is not true, right?

[Greg Heath]

No. You only assume a numerical order.

Training will find the correct weights.

For example, if you used 1,2,3,10 you should get the same answer because during training, the net will learn to decrease the input weights for variable four by a factor of 2.5