Journal ArticleDOI
Floating search methods in feature selection
TLDR
Sequential search methods characterized by a dynamically changing number of features included or eliminated at each step, henceforth "floating" methods, are presented and are shown to give very good results and to be computationally more effective than the branch and bound method.About:
This article is published in Pattern Recognition Letters.The article was published on 1994-11-01. It has received 3104 citations till now. The article focuses on the topics: Beam search & Jump search.read more
Citations
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Journal ArticleDOI
Simultaneous feature selection and parameter optimisation using an artificial ant colony: case study of melting point prediction
TL;DR: With a careful choice of objective function, the WAAC algorithm can be used to optimise machine learning and regression models that suffer from overfitting.
Journal ArticleDOI
Dynamic Time Warping for Music Retrieval Using Time Series Modeling of Musical Emotions
TL;DR: Experimental results demonstrate the benefits of MDT to predict time-varying musical emotions, and the proposed method for music retrieval based on emotion dynamics outperforms retrieval methods based on acoustic features.
Journal ArticleDOI
Protein Secondary Structure Prediction: A Review of Progress and Directions
TL;DR: The progress of the prediction methods over the years is depicted and sources of improvement are identified and further research directions are outlined.
Journal ArticleDOI
Discriminative multi-task feature selection for multi-modality classification of Alzheimer’s disease
TL;DR: The proposed discriminative multi-task feature selection method has potential to discover the disease-related biomarkers useful for diagnosis of disease, along with the comparison to several state-of-the-art methods for multi-modality based AD/MCI classification.
Proceedings ArticleDOI
MobILive 2014 - Mobile Iris Liveness Detection Competition
TL;DR: A brief description of the methods and the results achieved by the six participants in the 1st Mobile Iris Liveness Detection Competition (MobILive) is presented.
References
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Journal ArticleDOI
A Branch and Bound Algorithm for Feature Subset Selection
TL;DR: In this paper, a branch and bound-based feature subset selection algorithm is proposed to select the best subset of m features from an n-feature set without exhaustive search, which is computationally computationally unfeasible.
Journal ArticleDOI
A note on genetic algorithms for large-scale feature selection
W. Siedlecki,Jack Sklansky +1 more
TL;DR: The preliminary results suggest that GA is a powerful means of reducing the time for finding near-optimal subsets of features from large sets.
Journal ArticleDOI
A Direct Method of Nonparametric Measurement Selection
TL;DR: A direct method of measurement selection is proposed to determine the best subset of d measurements out of a set of D total measurements, using a nonparametric estimate of the probability of error given a finite design sample set.
Journal ArticleDOI
On the effectiveness of receptors in recognition systems
T. Marill,D. Green +1 more
TL;DR: Some of the theoretical problems encountered in trying to determine a more formal measure of the effectiveness of a set of tests are discussed; a measure which might be a practical substitute for the empirical evaluation.
Journal ArticleDOI
On automatic feature selection
W. Siedlecki,Jack Sklansky +1 more
TL;DR: In this paper, a review of feature selection for multidimensional pattern classification is presented, and the potential benefits of Monte Carlo approaches such as simulated annealing and genetic algorithms are compared.