Results 21 to 30 of about 6,969,735 (365)
Journal of Applied Science and Technology Trends, 2020 Due to sharp increases in data dimensions, working on every data mining or machine learning (ML) task requires more efficient techniques to get the desired results.
R. Zebari +4 more
semanticscholar +1 more source
A Multi-Scale Feature Selection Method for Steganalytic Feature GFR
IEEE Access, 2020 The Rich Model of the Gabor filter (referred to as the GFR steganalytic feature) can detect JPEG-adaptive steganography objects. However, feature dimensionality that is too high will lead to too much computation and will correspondingly reduce the ...
Xinquan Yu +4 more
doaj +1 more source
Weighted Heuristic Ensemble of Filters [PDF]
, 2015 Feature selection has become increasingly important in data mining in recent years due to the rapid increase in the dimensionality of big data. However, the reliability and consistency of feature selection methods (filters) vary considerably on different
Aldehim, Ghadah, Wang, Wenjia
core +1 more source
Forests, 2021 Increasing numbers of explanatory variables tend to result in information redundancy and “dimensional disaster” in the quantitative remote sensing of forest aboveground biomass (AGB).
Mi Luo +6 more
semanticscholar +1 more source
Efficient Multi-Label Feature Selection Using Entropy-Based Label Selection
Entropy, 2016 Multi-label feature selection is designed to select a subset of features according to their importance to multiple labels. This task can be achieved by ranking the dependencies of features and selecting the features with the highest rankings.
Jaesung Lee, Dae-Won Kim
doaj +1 more source
mixOmics: An R package for ‘omics feature selection and multiple data integration
bioRxiv, 2017 The advent of high throughput technologies has led to a wealth of publicly available ‘omics data coming from different sources, such as transcriptomics, proteomics, metabolomics.
F. Rohart +3 more
semanticscholar +1 more source
International Journal of Islamic Business and Economics (IJIBEC), 2017 Credit is one of the modern economic behaviors. In practice, credit can be either borrowing a certain amount of money or purchasing goods with a gradual payment process and within an agreed timeframe.
Ivandari Ivandari +3 more
doaj +1 more source
Feature Selection Using Neighborhood based Entropy [PDF]
Journal of Universal Computer Science, 2022 Feature selection plays an important role as a preprocessing step for pattern recognition and machine learning. The goal of feature selection is to determine an optimal subset of relevant features out of a large number of features.
Fatemeh Farnaghi-Zadeh +2 more
doaj +3 more sources
Streamwise feature selection [PDF]
Journal of Machine Learning Research, 2006 Summary: In streamwise feature selection, new features are sequentially considered for addition to a predictive model. When the space of potential features is large, streamwise feature selection offers many advantages over traditional feature selection methods, which assume that all features are known in advance.
Zhou, Jing +3 more
openaire +3 more sources
Feature Selection with the Boruta Package
, 2010 This article describes a R package Boruta, implementing a novel feature selection algorithm for finding emph{all relevant variables}. The algorithm is designed as a wrapper around a Random Forest classification algorithm.
M. Kursa, W. Rudnicki
semanticscholar +1 more source