Results 21 to 30 of about 717,161 (269)

Metalearning for Feature Selection

CoRR, 2017
A general formulation of optimization problems in which various candidate solutions may use different feature-sets is presented, encompassing supervised classification, automated program learning and other cases. A novel characterization of the concept of a "good quality feature" for such an optimization problem is provided; and a proposal regarding ...
Ben Goertzel, Nil Geisweiller, Chris Poulin   +2 more
openaire   +2 more sources

Quadratic Mutual Information Feature Selection

Entropy, 2017
We propose a novel feature selection method based on quadratic mutual information which has its roots in Cauchy–Schwarz divergence and Renyi entropy. The method uses the direct estimation of quadratic mutual information from data samples using Gaussian ...
Davor Sluga, Uroš Lotrič
doaj   +1 more source

CBFS: high performance feature selection algorithm based on feature clearness. [PDF]

PLoS ONE, 2012
BACKGROUND: The goal of feature selection is to select useful features and simultaneously exclude garbage features from a given dataset for classification purposes.
Minseok Seo, Sejong Oh
doaj   +1 more source

Semi-supervised Partial Multi-label Feature Selection [PDF]

Jisuanji kexue
Multi-label feature selection is a technique for reducing feature dimensionality by filtering out a subset of features with distinguishing power from the original feature space.However,the traditional method faces the problem of labeling accuracy ...
WU You, WANG Jing, LI Peipei, HU Xuegang
doaj   +1 more source

Threshold Adaptation for Improved Wrapper-Based Evolutionary Feature Selection

Biomimetics
Feature selection is essential for enhancing classification accuracy, reducing overfitting, and improving interpretability in high-dimensional datasets.
Uroš Mlakar, Iztok Fister, Iztok Fister
doaj   +1 more source

Supervised Feature Selection With a Stratified Feature Weighting Method

IEEE Access, 2018
Feature selection has been a powerful tool to handle high-dimensional data. Most of these methods are biased toward the highest rank features which may be highly correlated with each other.
Renjie Chen, Ning Sun, Xiaojun Chen, Min Yang, Qingyao Wu   +4 more
doaj   +1 more source

A feature selection method with feature ranking using genetic programming

Connection Science, 2022
Feature selection is a data processing method which aims to select effective feature subsets from original features. Feature selection based on evolutionary computation (EC) algorithms can often achieve better classification performance because of their ...
Guopeng Liu, Jianbin Ma, Tongle Hu, Xiaoying Gao   +3 more
doaj   +1 more source

Feature Importance in Gradient Boosting Trees with Cross-Validation Feature Selection

Entropy, 2022
Gradient Boosting Machines (GBM) are among the go-to algorithms on tabular data, which produce state-of-the-art results in many prediction tasks. Despite its popularity, the GBM framework suffers from a fundamental flaw in its base learners. Specifically,
Afek Ilay Adler, Amichai Painsky
doaj   +1 more source

Neighborhood Ranking-Based Feature Selection

IEEE Access
This article aims to integrate ${k}$ -NN regression, false-nearest neighborhood (FNN), and trustworthiness and continuity (T&C) neighborhood-based measures into an efficient and robust feature selection method to support the identification of ...
Adam Ipkovich, Janos Abonyi
doaj   +1 more source

Biological Invasion-Based Feature Selection Algorithm [PDF]

Jisuanji gongcheng
In nature, biological invasions have attracted attention because of their rapid development and significant ecological impacts. The introduction of populations to search for suitable habitats often has inherent logic, and communication between ...
ZHANG Jian, ZHANG Bo
doaj   +1 more source