So far, we have been able to change many features of our neural network include the feting network,
we also change the training function, the performance function.
But how about the plot function?
Let me run the program one more time.
As you can see, there are some information that I haven't seen them in this code like Époque time performance
gradient.
How can I change these parameters?
Let's see.
Back to the command window.
Let's type net to see different parameters and features the government has, this is actually a very
long list.
This is a name and some other data, a scroll down until we see airports.
Times go mean wait anymore.
These are in the train Parang.
That's what I'm looking for.
And I want to change type net dot parum.
Oh sure.
It should be twin porro.
Let's back here.
Let me check it again.
Train for the net.
That train.
There are several parameters and functions that we can change here.
The first one is show window.
Show window is true.
When I'm running the program, the window that we can see, it's just that we can just control it and
turn to the fall so we won't see it anymore.
So let me start with show window and see how it can change over program.
I'm going to start typing in here from the net.
I'm looking for trained Parap net.
That train is a big program and then dot this time showed just type it exactly as you see Linda.
I want it to be false.
Let's try it again, OK?
The only window that showed up was the custom neural network.
But the other window can see it here.
Now, let's try different parameters.
If you don't want to see this val performance test performance every time you can come here and make
them as a command.
And performance here and again, OK, I won't see any of this information in my command was the only
thing that happened was my neural network back again here.
Never stopped trying
to check different parameters.
The next one that I want to show is show command line.
This is false.
As you can see, the statue's already changed from true to false.
Next one that I want to change is a show command line typed here.
Next Dot, Twain or DOT.
Show, command line.
Equals to true.
OK, let's run the program one more time.
Very well.
I can see some information here like training depot and a training time and performance degrading,
demeaning in some other information.
Let's try this one again.
It also says that in a command line, it's just going to show the frequency of twenty five.
It means every twenty five times every twenty five, it will show it in a command.
Let me change this one to ten or we can change it to one.
But give me a swordfight 10 again that doesn't train from show to one.
So I should be able to see all the training information is let me run it here.
If you don't want to see this window anymore and then you need to make this one as a command as well,
the unit does make it as a command.
And here we can see all the training.
We can see the Époque time performance gradient, all the information that we were able to see in a
graphical user interface before this time.
We can see that for all the epochs that we had before, here they are.
Twenty eight Époque have actually more from zero is starting from zero.
You can use this information for analyzing your data and you can actually use them in a very good way.
Now go back to the command box and type NetJets Train Prall.
Here is the number of epochs.
It means these next four can train itself up to 1000 times.
If it reached 1000 times and didn't stop by any other parameters, then it stopped training.
It means we won't have any results.
So it's already 1000 times stop the training.
But what if we want to have something less like just tried four, four times and after that, if you
didn't get a new result just to stop the training.
So let me show it to you here.
Next, dot train haraam dot, this time airports equal to five.
Only train this network for five times, and after that it should stopped raining.
Change this one back to true, because I like to see the graphical user interface and this one, I don't
need it back to false.
Tonette Dortch, train product Epagogix five, now let's run the program here we can see the maximum
Époque reached five iteration was the maximum number of times that I let my neural network to train
itself and after five times training Idriz to stop their process of training.
Well, you can see that we can change any of these parameters, the other parameter, and then you can
change it a time.
There is no time here.
Let me show you.
Show it to you in a parameters for the time we have infinity.
If you want to train your network in a certain time, suppose you have many data.
The number of your data is a lot, actually.
The number of samples then you have any you want to limit the time that your P C trains the network.
You want to have it only for three minutes or five minutes, then you can just limited here to use net
train program.
Dot time equals two, for example, five minutes or next one is a goal.
The performance goal.
This is zero.
It means if the network reached zero error, Dennis, stop the training because that's the best scenario
and best situation that we have.
But in reality, we really cannot reach zero, especially if you are having some samples like for the
held parameters for a stress level of the students or some data like that, we can't really reach Zwarte.
Let me put this back to 1000 letters, 100 because five is not enough at all, train all that gold I
can set a goal for.
Zero point, maybe zero zero three, something like that, or let's.
We can see that it has already said the performance to zero point zero zero one where we go, what else
we have here, we have the mean gradient and more information that you can change them based on a data
base and samples that you have and the type of your data.
In the next session, I'm going to discuss Dysport to see you on the next session.