A parameter-free hybrid instance selection algorithm based on local sets with natural neighbors
Sign Up to like & getrecommendations! Published in 2020 at "Applied Intelligence"
DOI: 10.1007/s10489-019-01598-y
Abstract: Instance selection aims to search for the best patterns in the training set and main instance selection methods include condensation methods, edition methods and hybrid methods. Hybrid methods combine advantages of both edition methods and… read more here.
Keywords: natural neighbors; instance selection; parameter free; free hybrid ... See more keywords
Deep multiple instance selection
Sign Up to like & getrecommendations! Published in 2021 at "Science China Information Sciences"
DOI: 10.1007/s11432-020-3117-3
Abstract: Multiple instance learning (MIL) assigns a single class label to a bag of instances tailored for some real-world applications such as drug activity prediction. Classical MIL methods focus on figuring out interested instances, that is,… read more here.
Keywords: selection deep; multiple instance; selection; instance selection ... See more keywords
Effect of the distance functions on the distance-based instance selection for the feed-forward neural network
Sign Up to like & getrecommendations! Published in 2021 at "Evolutionary Intelligence"
DOI: 10.1007/s12065-021-00607-9
Abstract: The distance-based instance selection algorithm for the feed-forward neural network is a numerosity reduction technique. It selects only the instances at the decision boundary between consecutive classes of data to lessen the number of instances… read more here.
Keywords: distance; distance based; selection; based instance ... See more keywords
Data cleaning issues in class imbalanced datasets: instance selection and missing values imputation for one-class classifiers
Sign Up to like & getrecommendations! Published in 2021 at "Drug Testing and Analysis"
DOI: 10.1108/dta-01-2021-0027
Abstract: PurposeClass imbalance learning, which exists in many domain problem datasets, is an important research topic in data mining and machine learning. One-class classification techniques, which aim to identify anomalies as the minority class from the… read more here.
Keywords: class; class classifiers; one class; instance selection ... See more keywords
Unsupervised Dual Learning for Feature and Instance Selection
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3024690
Abstract: Feature selection and instance selection are dual operations on a data matrix. Feature selection aims at selecting a subset of relevant and informative features from original feature space, while instance selection at identifying a subset… read more here.
Keywords: feature selection; feature; feature instance; selection ... See more keywords
Instance Selection-Based Surrogate-Assisted Genetic Programming for Feature Learning in Image Classification.
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on cybernetics"
DOI: 10.1109/tcyb.2021.3105696
Abstract: Genetic programming (GP) has been applied to feature learning for image classification and achieved promising results. However, many GP-based feature learning algorithms are computationally expensive due to a large number of expensive fitness evaluations, especially… read more here.
Keywords: instance selection; training; feature learning; surrogate ... See more keywords
Ensembles of instance selection methods: A comparative study
Sign Up to like & getrecommendations! Published in 2019 at "International Journal of Applied Mathematics and Computer Science"
DOI: 10.2478/amcs-2019-0012
Abstract: Abstract Instance selection is often performed as one of the preprocessing methods which, along with feature selection, allows a significant reduction in computational complexity and an increase in prediction accuracy. So far, only few authors… read more here.
Keywords: ensembles instance; accuracy; selection; instance selection ... See more keywords