I need some research articles to cite for proving / emphasizing that feature selection or reduction improves classifier performance and prevents overfitting.
One of the most cited papers in the field is the following:
Guyon, Isabelle, and André Elisseeff. "An introduction to variable and feature selection." The Journal of Machine Learning Research 3 (2003): 1157-1182.
Actually, it serves as a review for a special session of the journal, but it is very well written and it covers a large array of topics.
I can provide some of my own papers:
J.M Banda and R.A Angryk “Selection of Image Parameters as the First Step Towards Creating a CBIR System for the Solar Dynamics Observatory”. International Conference on Digital Image Computing: Techniques and Applications (DICTA). Sydney, Australia, December 1-3, 2010. pp. 528-534.
J.M Banda and R.A Angryk “An Experimental Evaluation of Popular Image Parameters for Monochromatic Solar Image categorization” Proceedings of the twenty-third international Florida Artificial Intelligence Research Society conference (FLAIRS-23), Daytona Beach, Florida, USA, May 19–21 2010. pp. 380-385.
They both talk about what you are mentioning.
Well, the topic of the papers is related to speech recognition. Nevertheless, they deal with feature selection.
Anagnostopoulos, C.-N.; T. Iliou & I. Giannoukos (2012). ‘Features and classi-
fiers for emotion recognition from speech: a survey from 2000 to 2011’. In:
Artificial Intelligence Review. without issue assignment, pp. 1–23.
Hübner, D.; B. Vlasenko; T. Grosser & A. Wendemuth (2010). ‘Determining
optimal features for emotion recognition from speech by applying an evol-
utionary algorithm’. In: INTERSPEECH-2010. Makuhari, Japan: ISCA,
pp. 2358–2361.
Böck, R.; D. Hübner & A. Wendemuth (2010). ‘Determining Optimal Signal Fea-
tures and Parameters for HMM-Based Emotion Classification’. In: Proceed-
ings of the 15th IEEE Mediterranean Electrotechnical Conference. Valletta,
Malta: IEEE, pp. 1586–1590.
Schuller, B.; A. Batliner; S. Steidl & D. Seppi (2011c). ‘Recognising realistic
emotions and affect in speech: State of the art and lessons learnt from the
first challenge’. In: Speech Communication 53.9-10, pp. 1062–1087.
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