This is over, no real fighting.
This is good to solve and input output feting problem with a two layer feet forward.
No, we're all network feed is the architecture of this model of this network network.
And it has only two layer, one hidden layer and other outputs layer.
But we can adjust the number of neurons here for the hidden layer, only for the output layer it will
get only one.
I will explain it later.
So let's take a look at this one again.
We have input the input.
We'll get a specific way here.
We can adjust the weight, adjust the number of neurons in this heat and LEGARE then the output is going
to another layer with a specific rate.
And finally, we will have our output.
There are some explanation here as well.
You can just read them for your information.
Some of them are important.
For example, this network is using back propagation algorithm.
This is a name of algorithm.
Death has been used for these neural network beta next.
And here this is the part that we need to select the data.
We can select our input and we can select our target data or our output data.
If I choose this one, if I just click on inputs, I can see the variables from working space X and
Y, so I'm going to choose X for my input and the targets.
Let's just click on it.
If you have another data.
I just generated some samples in a matlab, but usually you will have some data maybe in Excel, Fi
or any other files.
You can just click to import your data, input your inputs and import your target data.
Our target data is why?
So I'm going to choose why samples are in Imitrex columns or in Imitrex rows.
What does it mean?
Let's back to our command window.
I'm going to just type Steel C to clear this work.
Now let's see what over X input.
Just Type X and inter.
These are the inputs I have 20 samples are just generated, 20 samples for X and then my Y, which is
the size of X.
Just click on Y and enter.
I have twenty output of twenty sample for Y as well.
You can also see X and Y together, X and Y for each sample.
Here it is X and Y.
By looking at this one, what can you understand.
Do you think they are now rows or do you think they're over samples.
Over data on columns.
OK, I assume that you are giving me a correct answer.
They are.
And columns.
Look at this one.
This is one sample, this is another sample and we have 20 of them.
These are inputs and outputs.
If you are using an Excel file, usually an Excel file, we do something else.
Let's take a look at this example.
This is how we usually put the data on the Excel flight.
This is a column for our inputs, another column for Y and output, meaning each sample will be here
under row.
This is one road, second row, third road.
If your data is something like that, then you need to choose the road metrics route.
But for our example, which is our samples are on the columns here, as you can see.
And the first row in this part is input X, second row is output Y.
Let's back to that.
We're waiting to hear I can see Matrix columns.
It has been selected as default.
I'm not going to change it.
Let's leave it there.
What else do we have?
It's a summary which gives us some information.
Input X is one to twenty metrics representing a static data.
Twenty samples of one element.
We have another element which it also has twenty samples.
That's just click on next and go to the next part.