I saw that the tool weka is having a gui interface. This gui interface is very easy for non coding users to classify data sets into classes. Matlab is very difficult since say for example making a neural network you need to write code and to do that you need to have a solid understanding of whats going on. Are there other tools like weka or else is there a plugin to matlab that gives more power to it?
RapidMiner has a functional GUI, and will work for both classification and clustering. It is the most popular open-source (free) data mining application available as of 2012.
RapidMiner: http://rapid-i.com/
It also has numerous training videos and tutorials that you can follow along with - I learned basic clustering methods using a K-means cluster method in about 3 hours. See the Vancouver Data blog for some great RapidMiner analytics videos. Top-notch stuff, really.
Vancouver Data (Neil McGuigan): http://vancouverdata.blogspot.com/
As a bonus, you can install the Weka plug-in, which then gives you GUI Weka. All of the add-ons are free and well-integrated. Other add-ons include a GUI 'R' (the stats program), Reporting Services, Text and Web Analytics, etc. It is fairly simple to use straight 'out of the box' (IMO).
Weka is very (very) powerful and you can write your own classifier if that's what you need to do.
Between Matlab and Weka there's pretty much nothing you can't do in terms of Machine Learning.
You might want to check out Netlab toolkit for Matlab, which is a neural network toolkit developed by a Professor at Aston University - it is available from http://www1.aston.ac.uk/eas/research/groups/ncrg/resources/netlab/
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I am very new in this field and I would like to create a Neural Network to classify a dataset that I have in MongoDB. I would like some advise about where should I start, what technology should I use or any tutorial that you think it can help.
If you know about any open source code that already does this, I would love to take a look at it.
Thank you !!
Pick a platform
In essence, you should pick a platform or framework that does much of the dirty work for you and read up on some tutorials for that.
The big choice is between natural language processing frameworks such as NLTK or spaCy or Stanford NLP tools; or a generic machine learning framework such as Tensorflow or PyTorch.
Text classification is a popular task that's reasonably entry-level, is well supported by pretty much everything (so it's not much to say there in a shopping question, pick whatever you like) and would have a bunch of tutorials available online for any major platform.
I will take my graduation project next semester , I decide to complete my high degrees studying ,because I'm from low-income people , I want to dive on anything that helps me to do a paper or research or something supports my situation to gain scholarship.
my supervisor suggests that intrusion detection system using neural network is suitable for me , and he will help me , but I need to know fundamentals on this field .
there is limited resources on this topic , just thesis , papers and researches talk about only overview on IDs using neural network .
can anyone provides me some resources and references introduce me to
intrusion detection system using neural network to learn the fundamentals and basic ?
First, some background; Neural nets are by design black box. It is less important to understand the problem you are solving when designing a neural network than it is when writing a deterministic algorithm to solve it directly. With that in mind, you probably don't need to learn about "intrusion detection systems using neural networks", but would probably benefit more from learning about neural networks and intrusion systems separately.
I will leave it to you to find texts on intrusion detection systems, but would recommend reading the following to get started on what neural networks are, and how they work:
Neural Networks - A Systematic Introduction
If you think you have understood the basis of neural networks conceptually, you will want to learn a programming language. Your options diverge somewhat at this point, but I would suggest that if you want to learn neural nets from an academic perspective and want to have more control over the design and guts of the program, you would probably benefit most from learning C++. There is a wealth of knowledge on the topic of learning C++ online. In fact, probably the most popular page on this website is dedicated to that topic:
The Definitive C++ Book Guide and List
Once you understand neural network fundamentals and C++, the world is your oyster! If you're feeling adventurous, have a look at Kenneth Stanley's NEAT algorithm. The source code will teach you a lot about neural net algorithms.
From here to creating a learning machine that understands intrusion attempts is almost trivial from a programming perspective. You really just need to get the data, which may be really easy or really hard, but your supervisor should be able to help you find data sources on which to train the network once you reach this point.
Good luck!
We are a group of students of chemical engineering mostly proficient in MATLAB and Simulink but with almost no clue of web programming.
Our idea is to develop some online examples by using interactive graphics with dynamic effects and 2D/3D simulations. We know that MATLAB has some solutions but the compilers are not available for the student version. Furthermore, we want to promote the use of free open source alternatives (SciLab, Octave, NumPy)
Ideally, we would like to use a 4GL which includes a free library for numeric analysis and combine it with graphic user interface framework for web applications.
An good example will be Easy Java Simulations that generates java code and can be easily implemented online. However, we are looking for something that can be executed without java or another plugin (see google chart tool)
Although we are willing to learn (Python, Java), we would like to start with the easiest solution towards a painless transition for a chemical engineer ;)
We will really appreciate our recommendations and suggestions!
Your best shot is to buy the product Matlab Builder NE. You can use WebFigures to seamlessly create web applications from your Matlab application.
I’m looking a simple tool to train and test neural networks for classification tasks. It need not be very sophisticated tool and I just want to train and test simple data sets such as given in the following web site.
http://www.stats.ox.ac.uk/pub/PRNN/
It's not a pre-made utility, but you could roll your own quite quickly using the Encog neural network framework (for both Java and .NET).
I've used it before and it was quite easy to get to grips with. The documentation is quite good, and if you need it, I've also found support on the forums to be good.
* UPDATE *
I just remembered that Encog does actually ship with a pre-made utility called Encog Workbench, which should do what you want.
Firstly, I am a beginner in artificial neural networks and I need a special library for training the artificial neural networks, but I very confused in the selection of the library, and since I didn't have the experience I wanted to consult you.
I have read about three libraries:
FANN, Flood, and Neuro Fusion libraries.
So, what are you think about the easiest and Least problems library for using it with VC++.6?
I just started using FANN, and it seems to be very well documented, with great examples and fast.
It operates with floats/doubles/integers and implements the Cascade2 training method, which is really great if you are unsure about the architecture of your NN.
It is not as rich as Encog (didn't use it), but if FANN implements all the functionalities you need, I think you should go with it.
Edit: I just realized that Encog is only available for .NET C# (besides Java)