Results 31 to 40 of about 7,765,049 (335)

New Feature Selection Algorithm Based on Feature Stability and Correlation

IEEE Access, 2022
The analysis of a large amount of data with high dimensionality of rows and columns increases the load of machine learning algorithms. Such data are likely to have noise and consequently, obstruct the performance of machine learning algorithms.
Luai Al-Shalabi
doaj   +1 more source

Stable Feature Selection for Biomarker Discovery [PDF]

, 2010
Feature selection techniques have been used as the workhorse in biomarker discovery applications for a long time. Surprisingly, the stability of feature selection with respect to sampling variations has long been under-considered.
He, Zengyou, Yu, Weichuan
core   +2 more sources

Feature Selection: A Review and Comparative Study

E3S Web of Conferences, 2022
Feature selection (FS) is an important research topic in the area of data mining and machine learning. FS aims at dealing with the high dimensionality problem.
Younes Bouchlaghem, Yassine Akhiat, Souad Amjad   +2 more
semanticscholar   +1 more source

Feature extraction for epileptic seizure detection using machine learning

Current Medicine Research and Practice, 2020
Background: Epilepsy is a common neurological disorder and affects approximately 70 million people worldwide. The traditional approach used by neurologists for the detection of seizure is time consuming.
Renuka Mohan Khati, Rajesh Ingle
doaj   +1 more source

Feature selection guided by structural information [PDF]

, 2009
In generalized linear regression problems with an abundant number of features, lasso-type regularization which imposes an $\ell^1$-constraint on the regression coefficients has become a widely established technique.
Castell, Wolfgang zu, Slawski, Martin, Tutz, Gerhard   +2 more
core   +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

Improving feature selection algorithms using normalised feature histograms

, 2011
The proposed feature selection method builds a histogram of the most stable features from random subsets of a training set and ranks the features based on a classifier based cross-validation.
A.K. Maan, A.P. James, Fan, Hall
core   +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

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