Archive for the ‘Spectral Feature Selection’ Category

New Techniques Turbo-Charge Data Mining

Wednesday, January 11th, 2012

New Techniques Turbo-Charge Data Mining by Nicole Hemsoth.

From the post:

While the phrase “spectral feature selection” may sound cryptic (if not ghostly) this concept is finding a welcome home in the realm of high performance data mining.

We talked with an expert in the spectral feature selection for data mining arena, Zheng Zhao from the SAS Institute, about how trends like this, as well as a host of other new developments, are reshaping data mining for both researchers and industry users.

Zhao says that when it comes to major trends in data mining, cloud and Hadoop represent the key to the future. These developments, he says, offer the high performance data mining tools required to tackle the types of large-scale problems that are becoming more prevalent.

In an interview this week, Zhao predicted that over the next few years, large-scale analytics will be at the forefront of both academic research and industry R&D efforts. On one side, industry has strong requirements for new techniques, software and hardware for solving their real problems at the large scale, while on the other hand, academics find this to be an area laden with interesting new challenges to pursue.

For more details, you may want to see our earlier posts:

Spectral Feature Selection for Data Mining

Spectral Graph Theory

Spectral Graph Theory

Friday, December 30th, 2011

Spectral Graph Theory by Fan R K Chung.

A developing area of mathematics that may be important for high dimensional data mining. Relevant to the spectral feature selection post from yesterday.

You can see the first four revised chapters and the bibliography at: Spectral Graph Theory (revised and improved)

Spectral Feature Selection for Data Mining

Thursday, December 29th, 2011

Spectral Feature Selection for Data Mining by Zheng Alan Zhao and Huan Liu.

I did not find the publisher’s description all that helpful.

You may want to review:

The supplemental page maintained by the authors, Spectral Feature Selection for Data Mining. There you will also find source code by chapter in Matlab format and some other materials.

Earlier work by the authors, see:

Spectral feature selection for supervised and unsupervised learning (2007) by Zheng Zhao , Huan Liu.

Slow going but the early work appears to hold a great deal of promise.

If you have or get a copy of the book, please forward or point to your comments.