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Feature Extraction 2006
- Isabelle Guyon, Masoud Nikravesh, Steve R. Gunn, Lotfi A. Zadeh:
Feature Extraction - Foundations and Applications. Studies in Fuzziness and Soft Computing 207, Springer 2006, ISBN 978-3-540-35487-1 - Isabelle Guyon, André Elisseeff:
An Introduction to Feature Extraction. 1-25 - Norbert Jankowski, Krzysztof Grabczewski:
Learning Machines. 29-64 - Gérard Dreyfus, Isabelle Guyon:
Assessment Methods. 65-88 - Wlodzislaw Duch:
Filter Methods. 89-117 - Juha Reunanen:
Search Strategies. 119-136 - Thomas Navin Lal, Olivier Chapelle, Jason Weston, André Elisseeff:
Embedded Methods. 137-165 - Kari Torkkola:
Information-Theoretic Methods. 167-185 - Eugene Tuv:
Ensemble Learning. 187-204 - Madan M. Gupta, Noriyasu Homma, Zeng-Guang Hou:
Fuzzy Neural Networks. 205-233 - Isabelle Guyon, Steve R. Gunn, Asa Ben-Hur
, Gideon Dror:
Design and Analysis of the NIPS2003 Challenge. 237-263 - Radford M. Neal, Jianguo Zhang:
High Dimensional Classification with Bayesian Neural Networks and Dirichlet Diffusion Trees. 265-296 - Kari Torkkola, Eugene Tuv:
Ensembles of Regularized Least Squares Classifiers for High-Dimensional Problems. 297-313 - Yi-Wei Chen, Chih-Jen Lin:
Combining SVMs with Various Feature Selection Strategies. 315-324 - Zhili Wu, Chun-hung Li:
Feature Selection with Transductive Support Vector Machines. 325-341 - Amir Reza Saffari Azar Alamdari:
Variable Selection using Correlation and Single Variable Classifier Methods: Applications. 343-358 - Alexander Borisov, Victor Eruhimov, Eugene Tuv:
Tree-Based Ensembles with Dynamic Soft Feature Selection. 359-374 - Saharon Rosset, Ji Zhu:
Sparse, Flexible and Efficient Modeling using L 1 Regularization. 375-394 - Ran Gilad-Bachrach
Margin Based Feature Selection and Infogain with Standard Classifiers. 395-401 - Wei Chu, S. Sathiya Keerthi, Chong Jin Ong
Bayesian Support Vector Machines for Feature Ranking and Selection. 403-418 - Sepp Hochreiter, Klaus Obermayer:
Nonlinear Feature Selection with the Potential Support Vector Machine. 419-438 - Thomas Navin Lal, Olivier Chapelle, Bernhard Schölkopf:
Combining a Filter Method with SVMs. 439-445 - Mark J. Embrechts, Robert A. Bress, Robert H. Kewley:
Feature Selection via Sensitivity Analysis with Direct Kernel PLS. 447-462 - Danny Roobaert, Grigoris I. Karakoulas, Nitesh V. Chawla
Information Gain, Correlation and Support Vector Machines. 463-470 - Krzysztof Grabczewski, Norbert Jankowski:
Mining for Complex Models Comprising Feature Selection and Classification. 471-488 - Sang-Kyun Lee, Seung-Joon Yi, Byoung-Tak Zhang:
Combining Information-Based Supervised and Unsupervised Feature Selection. 489-498 - Marc Boullé:
An Enhanced Selective Naïve Bayes Method with Optimal Discretization. 499-507 - Vincent Lemaire, Fabrice Clérot:
An Input Variable Importance Definition based on Empirical Data Probability Distribution. 509-516 - Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux, Jean-François Paiement, Pascal Vincent, Marie Ouimet:
Spectral Dimensionality Reduction. 519-550 - Michinari Momma, Kristin P. Bennett:
Constructing Orthogonal Latent Features for Arbitrary Loss. 551-583 - Ran Gilad-Bachrach
Large Margin Principles for Feature Selection. 585-606 - Ilya Levner, Vadim Bulitko, Guohui Lin:
Feature Extraction for Classification of Proteomic Mass Spectra: A Comparative Study. 607-624 - Asa Ben-Hur
Sequence Motifs: Highly Predictive Features of Protein Function. 625-645
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