So this week there most of the time I spent it in my office, working

for a group meeting. Incredibly, I got into this stream of

productivity and finish my small toy example. This little experiment

gave us a chance to understand the main problems that will affect our

final task. Now we can focus in some extra experiments to corroborate

some of this hypothesis, and start writing the project formalization.

Most of the time have been spent in the development of quick

prototypes. Quick results is the most important thing, so I try to not

reinvent the wheel. Most of the time I finish using open source

libraries that already implement the most common algorithms for data

analysis. The three tools that have been most useful are:

libraries. Simple Clustering, Nearest Neighbor search, simple

classifiers and trees can be used for a quick visualization. The GUI

interface is great, but using the API can be sometimes really annoying.

functions for linear algebra solving, descriptive statistics and random number

generator. Is small and quick, so is always the one used in the final prototype.

for a group meeting. Incredibly, I got into this stream of

productivity and finish my small toy example. This little experiment

gave us a chance to understand the main problems that will affect our

final task. Now we can focus in some extra experiments to corroborate

some of this hypothesis, and start writing the project formalization.

Most of the time have been spent in the development of quick

prototypes. Quick results is the most important thing, so I try to not

reinvent the wheel. Most of the time I finish using open source

libraries that already implement the most common algorithms for data

analysis. The three tools that have been most useful are:

**Weka:**this library implements the most common machine learninglibraries. Simple Clustering, Nearest Neighbor search, simple

classifiers and trees can be used for a quick visualization. The GUI

interface is great, but using the API can be sometimes really annoying.

**Commons-Math:**I am using this one a lot lately. The library implementsfunctions for linear algebra solving, descriptive statistics and random number

generator. Is small and quick, so is always the one used in the final prototype.

The API is very clean so its really easy to add it to the main code.

The linear algebra section have some problems scaling for sparse

matrices. But If you only need some quick linear regression model, or

matrices. But If you only need some quick linear regression model, or

descriptive stats this is yourr tool.

do. Still, I am learning to love R with time. R have all the algorith

in Weka and Commons-Math, and much more. The number of libraries is

amazing and you don't need the pay the extra money that will cost for

other tools (We all know the main suspect).

To integrate R with Java, I use RServe. Before I used R for plotting

the final results, but lately I am also using the tool for data

analysis.

The documentation for all this libraries is good, and it they become

better with time.

best!!

**R:**good I hate the syntax of R. I can not describe how much Ido. Still, I am learning to love R with time. R have all the algorith

in Weka and Commons-Math, and much more. The number of libraries is

amazing and you don't need the pay the extra money that will cost for

other tools (We all know the main suspect).

To integrate R with Java, I use RServe. Before I used R for plotting

the final results, but lately I am also using the tool for data

analysis.

The documentation for all this libraries is good, and it they become

better with time.

**PS:**good luck to a very special person in her big date. I hope for thebest!!

## Comments

Eduardo Ruiz on Sunday, 17 July 2011, 10:05 EDT # |