Result Analysis of the NIPS 2003 Feature Selection Challenge

نویسندگان

  • Isabelle Guyon
  • Steve R. Gunn
  • Asa Ben-Hur
  • Gideon Dror
چکیده

The NIPS 2003 workshops included a feature selection competition organized by the authors. We provided participants with five datasets from different application domains and called for classification results using a minimal number of features. The competition took place over a period of 13 weeks and attracted 78 research groups. Participants were asked to make on-line submissions on the validation and test sets, with performance on the validation set being presented immediately to the participant and performance on the test set presented to the participants at the workshop. In total 1863 entries were made on the validation sets during the development period and 135 entries on all test sets for the final competition. The winners used a combination of Bayesian neural networks with ARD priors and Dirichlet diffusion trees. Other top entries used a variety of methods for feature selection, which combined filters and/or wrapper or embedded methods using Random Forests, kernel methods, or neural networks as a classification engine. The results of the benchmark (including the predictions made by the participants and the features they selected) and the scoring software are publicly available. The benchmark is available at www.nipsfsc.ecs.soton.ac.uk for post-challenge submissions to stimulate further research.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Combining SVMs with Various Feature Selection Strategies

This article investigates the performance of combining support vector machines (SVM) and various feature selection strategies. Some of them are filtertype approaches: general feature selection methods independent of SVM, and some are wrapper-type methods: modifications of SVM which can be used to select features. We apply these strategies while participating at NIPS 2003 Feature Selection Chall...

متن کامل

Feature Selection with the CLOP Package

We used the datasets of the NIPS 2003 challenge on feature selection as part of the practical work of an undergraduate course on feature extraction. The students were provided with a toolkit implemented in Matlab. Part of the course requirements was that they should outperform given baseline methods. The results were beyond expectations: the student matched or exceeded the performance of the be...

متن کامل

Competitive baseline methods set new standards for the NIPS 2003 feature selection benchmark

We used the datasets of the NIPS 2003 challenge on feature selection as part of the practical work of an undergraduate course on feature extraction. The students were provided with a toolkit implemented in Matlab. Part of the course requirements was that they should outperform given baseline methods. The results were beyond expectations: the student matched or exceeded the performance of the be...

متن کامل

Teaching machine learning from examples

We used the datasets of the NIPS 2003 challenge on feature selection as part of the practical work of an undergraduate course on feature extraction. The students were provided with a toolkit implemented in Matlab. Part of the course requirements was that they should outperform given baseline methods. The results were beyond expectations: the student matched or exceeded the performance of the be...

متن کامل

A New Hybrid Feature Subset Selection Algorithm for the Analysis of Ovarian Cancer Data Using Laser Mass Spectrum

Introduction: Amajor problem in the treatment of cancer is the lack of an appropriate method for the early diagnosis of the disease. The chemical reaction within an organ may be reflected in the form of proteomic patterns in the serum, sputum, or urine. Laser mass spectrometry is a valuable tool for extracting the proteomic patterns from biological samples. A major challenge in extracting such ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2004