scispace - formally typeset
Journal ArticleDOI

Floating search methods in feature selection

Pavel Pudil, +2 more
- 01 Nov 1994 - 
- Vol. 15, Iss: 11, pp 1119-1125
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
More filters
Journal ArticleDOI

First review on psoriasis severity risk stratification

TL;DR: The first state-of-the-art review of technology solicitation in psoriasis along with its current practices, challenges and assessment techniques is presented and it is concluded that CAD systems are promising for risk stratification and assessment of Psoriasis.
Journal ArticleDOI

Spectroscopic detection of rice leaf blast infection from asymptomatic to mild stages with integrated machine learning and feature selection

TL;DR: It is suggested that reflectance spectroscopy has great potential in the pre-visual detection of RLB infection and airborne or spaceborne imaging Spectroscopy is promising for the mapping of early occurrence and severity levels of R LB infection at large scales.
Journal ArticleDOI

Early survival prediction in non-small cell lung cancer from PET/CT images using an intra-tumor partitioning method

TL;DR: A novel feature set designed for capturing intra-tumor heterogeneity was introduced and Judging by their prognostic power, the proposed features have a promising potential for early survival prediction.
Journal ArticleDOI

Can Triaxial Accelerometry Accurately Recognize Inclined Walking Terrains

TL;DR: This paper investigates the benefits of automatic gait analysis approaches including step-by-step gait segmentation and heel-strike recognition of the accelerometry signal in classifying various gradients and aims to improve the accuracy of daily EE estimates with accurate measures on terrain inclinations.
Journal ArticleDOI

Ensemble of on-line signature matchers based on OverComplete feature generation

TL;DR: A novel method for building an ensemble of on-line signature verification systems based on one-class classifiers and the results show that the proposed ensemble outperforms the ensembles based only on the original features.
References
More filters
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

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

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

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.
Related Papers (5)