It is not required to have a software with parallel nature. The execution time will be only longer without affecting the data mining results. If you are working with big data (Thousands of gegabytes and more), having a parallel solution on Haddop can be a good solution. In addition, SQL Server has this parallel nature to leverage the power of all parallel processors to have a fast execution time for medium and large databases.

Using Matlab you can Speed up your code based on pre-allocation, vectorization, parfor, spmd....etc.

PRtools is a Matlab based library which is very easy to be used.

personally, I use Weka, it is written in Java and therefore your implementation can be written in different parallel and distributive ways. 

Hi Emin,

In my opinion, I recommend you to use R for Data mining, you will find a lot of packages that contain methods covering classification, clustering, association rules, ... etc, using different models. in addition to some helpful functions for data preparation.

easy to use, general, for any thing you want just include the needed package, very good for data visualization.

as Mr.Adrian mentioned Caret package is a helpful one, it includes many classification models, take a look at this Cheat sheet:

https://github.com/ziadbkh/Data-Mining/blob/master/Cheat%20Sheets/Caret%20Library.pdf

Good luck

Firstly, thank you, everyone, for your support, your quick responses and excellent assistance.I tried to use various classifiers in Weka. (I am using sparse matrix methods.) While getting familiar with Rotation Forest in Weka, I stumbled on an Overflow error. (I am using one pc and I changed the heap size in Weka as 6 GB)

I want to solve problems using Weka-Parallel. Weka-Parallel is more complicated because of its two worlds: port number and products required updated. I used R with KNN algorithm but I didn't used to do that with Rotation Forest. As you mentioned, that I can use R with Rotation Forest.

Best Regards

Emin Merhaba :)

bende R tavsiye ederim, öğrenmesi ilk etapta zor ama paketleri çok zengin, her istediğini bulabiliyorsun, selamlar.

Along with Weka tool you can use the Hadoop tool for big data analysis

Different software has different advantage. I like to use Python. But I also think Matlab, C++, R ... are all good tool in big data area.

Dear Emin,

You could use Rhadoop. 

Try to follow the contain of this resource if you read french.

http://www.math.univ-toulouse.fr/~besse/Wikistat/pdf/st-tutor5-R-mapreduce.pdf

Good luck.

Dear Emin,

You could use R for your data mining studies. you will find alot of packages regarding data mining.

R and Python are leaders of the pack , as far as opensource is concerned. While R has a great academic following, Python is more accepatable commercially. Both have wildly growing communities. It may be better to keep the data storage and modeling part separate, R, Python both offers some integration with Hadoop!

Thank you so much, all of you, for helping me move forward.

Best Regards

Dear Emin,

Please take a look at this study: https://www.datacamp.com/community/tutorials/r-or-python-for-data-analysis.

I recommend R with Hadoop for Big Data Analysis.

There are some tools for stream mining: 

WEKA

Orange with python 

Ggobi

Tangara

Knime

MOA, etc.

I hope that this information could help you.

Best regards.