Wednesday, January 28, 2009

Data Mining and Neural Networks (NN)

Dear Friends,
This is my first post of 2009... happy new year!
I have been absent this month because I’m writing the second chapter of my master's thesis. Anyway, today I’ll write a bit of neural networks, which are on of the most important and useful Data Mining techniques.

But what is a neural network? A Neural Network (NN) is a system composed of many simple processing elements operating in parallel which can acquire, store, and utilize experiential knowledge. As I told you before, I’m very fascinated with Data Mining and the intelligence we can get from it. You can use it in Financial Markets (is the theme of my master dissertation), on insurance, or medicine, on retail, on all activities!!! The topics below explain better where you can apply NN, the learning methods, types and an Arquitecture that a NN could has.

NN Applications
-Function approximation

NN Type
- Static (feed forward)
- Dynamic / Back-Propagation (feedback)

NN Arquitecture
- Single layer
- Multilayer
- Recurrent
- Self-organized

NN Learning Methods
- Supervised (network has inputs and their corresponding outputs)
- Unsupervised

In Data Mining classes directed by Professor Dr. Duarte Trigueiros, I did a practical excel exercise (homework) in order to better understand NN functionalities. I’ll share it with you today and feel free to contact me to get a copy of excel file. The excel files has the formulas behind and could be interesting if you think to improve your knowledge on this.

Initially, weights are random and the output of neural network will be compared to desired output. If same, reinforce patterns and if different, NN will adjust weights.

The dataset should be divided for training and testing, which in this case, because the NN is a supervised with back-propagation, the training dataset has the output classified and a better model will be created. After the model is created, the test dataset is considered as the input and the model could be evaluated.


Cioara Andrei said...

Foarte interesant ce ai postat.M-am uitat pe blogul tau si imi place ce am vazut chiar e frumos si interesant.Felicitari si sigur am sa mai revin!

Amin said...
This comment has been removed by the author.
Amin said...

Hi Pedro,

Happy new year,
I enjoy reading this post. Unfortunately, it was more than 7years ago that I passed AI course, and I couldn't remember anything about NN now :(
I think it would be very to know the algorithms for using them in a true situation.


vitorsilva said...

interesting. could you elaborate a bit more on the picture you posted?

like what is the relation between the expected result and the actual outputs.

and maybe give a practical example on using the method shown in the picture.

Pedro said...

hi Guys!
Data mining is the present and the future! :-)

I'm with you... This week I'm very busy finishing the chapter 2 of my master BI dissertation, but next week I will do it for you, and also send you the text mining docs that you asked for!

Cheers my friends Amin and Vitor!!!

endy said...

Have you any literature of great to me to know everything about Neural netwrok

Pedro said...

It's simple amazing! :-)

Anonymous said...

Hi pedro!!! I read your post regarding neural network and datmining... I m pursuing ME and was planning to go for thesis in " data mining based on neural networks". Could you please guide a little if there is any fresh scope in this topic !!!

bilou said...

hello pedro could you help me and send some leterture about BI touls or neural network

bilou said...

hi pedro happy new year 2010
i'm student from malsyia i need your help about neural network and BI tools
my mail

Pedro said...

Welcome to this blog!
I sent you an email!

dude said...

Hi Pedro,
Your article is very helpful I'm still looking for the excel file to know more with practice, would you send me.?
my email dude_boss[at]

thanks in advance

Dude said...

Hi Pedro,
Your article is very helpful I'm still looking for the excel file to know more with practice, would you send me.?
my email dude_boss[at]

thanks in advance


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