Why is Matlab the best language for data mining?

While starting a new project a few days ago, I had to answer the recurrent question: What language do I choose? In research, we have the opportunity of choosing any language, free or not. This is usually not the case in industry where the language can be fixed for many reasons (price, customer choice, boss choice, same as existing system, etc.).

I basically had to choose between Java and Matlab (C++ was soon deleted from my list since I don't like to spend time on pointers and manually free up the memory, but this is very personal). Of course a lot of others are available, but I feel more confident with these two. As most of my work was done with Matlab, I decided to start with Java. Contradictory? Not at all, I just wanted to know how easy it was to use Java for raw data mining tasks (i.e. without using JDM framework or such).

When doing data mining, a large part of the work is to manipulate data. Indeed, the part of coding the algorithm can be quite short since Matlab has a lot of toolboxes for data mining. And when manipulating data, Matlab is definitely better. It is normal since it is done to work with matrices (MATrix LABoratory). Thus, deleting a row, a column, transposing a matrix, calculating the determinant... all these can be done in one line of code. To my knowledge, this is not the case with Java, but if you know some way, feel free to comment.

For more information about using Matlab for data mining, the best place is Will's blog. In the next post, I will write about the other side of the coin and explain some of Matlab's drawbacks.

Continue reading... Sphere: Related Content

Java Data Mining (cont'd)

Java World has an article concerning the Java Data Mining book discussed on Data Mining Research. It contains a quite long excerpt of the book. This is useful for people interesting in reading a part of the book before buying it.

Continue reading... Sphere: Related Content

Small book review: Java Data Mining

Unlike usual books on data mining discussed in this blog, Java Data Mining is a book written for data mining practitioners. Even if the word Java appears in the title, practitioners of other languages or software may be interested by the first part of the book (Strategy), which is really worth reading. The other parts of the book focus on the JDM API itself (Standards), problem solving with case study (Practice) and finally evolution of standards in data mining (Wrapping Up).

Data mining is clearly defined and compared with other concepts such as OLAP. A very interesting comparison is made between data mining and gold mining. As written previously, this book is practitioner-oriented. Moreover, the focus is on data mining with customer related information. Another good thing is the data mining glossary at the end of the book which is welcomed. According to the book, automated data mining strategies are being developed at KXEN. A related discussion can be found on Data Mining Research.

References to Wikipedia are to my opinion not appropriate in a book. Recent improvements have made this encyclopedia more reliable. However, I would never use it as a serious reference since anybody can write articles on it. A strange choice has been made regarding the word data (singular instead of plural). These small details aren't significant in regard to the quality of the book. To conclude, data mining practitioners and people using Java for data mining should really consider this book.

Continue reading... Sphere: Related Content

Java data mining

Are you interested in data mining? Yes... you are reading this blog. Do you use to program in Java? If yes, then the book Java Data Mining can interest you. It is briefly described by KDnuggets. To my point of view, Java is perhaps not the best language to use for data mining. Either you are in the industry and need a fast running application; then you will certainly use C++ or .NET. Or you are doing research and you need more interactivity and simplicity while coding; then you will probably use MATLAB for example. Java is neither as fast as C++, nor as easy to use as MATLAB. Perhaps this book will tell you why to use Java for data mining. By the way, a good book on data mining (with Java examples) is Data Mining: Practical Machine Learning Tools and Techniques.

Continue reading... Sphere: Related Content