Ensemble feature selection for multi‐label text classification: An intelligent order statistics approach
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.23044
Abstract: Because of the overgrowth of data, especially in text format, the value and importance of multi‐label text classification have increased. Aside from this, preprocessing and particularly intelligent feature selection (FS) are the most important step… read more here.
Keywords: label text; order statistics; classification; multi ... See more keywords
Multi‐iPPseEvo: A Multi‐label Classifier for Identifying Human Phosphorylated Proteins by Incorporating Evolutionary Information into Chou′s General PseAAC via Grey System Theory
Sign Up to like & getrecommendations! Published in 2017 at "Molecular Informatics"
DOI: 10.1002/minf.201600085
Abstract: Predicting phosphorylation protein is a challenging problem, particularly when query proteins have multi‐label features meaning that they may be phosphorylated at two or more different type amino acids. In fact, human protein usually be phosphorylated… read more here.
Keywords: multi; system; multi label; multi ippseevo ... See more keywords
Machine learning based multi-label classification of single or mixed-composition urinary stones in in-vivo spectral CT.
Sign Up to like & getrecommendations! Published in 2022 at "Medical physics"
DOI: 10.1002/mp.16154
Abstract: BACKGROUND Urinary stones comprise both single and mixed compositions. Knowledge of the stone composition helps the urologists choose appropriate medical interventions for patients. The parameters from the spectral computerized tomography (CT) analysis have potential values… read more here.
Keywords: composition; multi label; label; label classification ... See more keywords
CT-based deep multi-label learning prediction model for outcome in patients with oropharyngeal squamous cell carcinoma.
Sign Up to like & getrecommendations! Published in 2023 at "Medical physics"
DOI: 10.1002/mp.16465
Abstract: BACKGROUND Personalized treatment is increasingly required for oropharyngeal squamous cell carcinoma (OPSCC) patients due to emerging new cancer subtypes and treatment options. Outcome prediction model can help identify low or high-risk patients who may be… read more here.
Keywords: outcome; test; prediction; multi label ... See more keywords
Multi-label classification of retinal lesions in diabetic retinopathy for automatic analysis of fundus fluorescein angiography based on deep learning
Sign Up to like & getrecommendations! Published in 2020 at "Graefe's Archive for Clinical and Experimental Ophthalmology"
DOI: 10.1007/s00417-019-04575-w
Abstract: Purpose To automatically detect and classify the lesions of diabetic retinopathy (DR) in fundus fluorescein angiography (FFA) images using deep learning algorithm through comparing 3 convolutional neural networks (CNNs). Methods A total of 4067 FFA… read more here.
Keywords: diabetic retinopathy; multi label; retinal lesions; lesions diabetic ... See more keywords
Stacking model of multi-label classification based on pruning strategies
Sign Up to like & getrecommendations! Published in 2018 at "Neural Computing and Applications"
DOI: 10.1007/s00521-018-3888-0
Abstract: Exploiting dependencies between the labels is the key of improving the performance of multi-label classification. In this paper, we divide the utilizing methods of label dependence into two groups from the perspective of different ways… read more here.
Keywords: label classification; multi label; feature;
Multi-label classifier for protein sequence using heuristic-based deep convolution neural network
Sign Up to like & getrecommendations! Published in 2021 at "Applied Intelligence"
DOI: 10.1007/s10489-021-02529-6
Abstract: Deep learning techniques are found very useful to classify sequential data in recent times. The protein sequences belong to the functional classes based on the structure of their sequences. The annotation task of protein sequences… read more here.
Keywords: protein; multi label; functional classes; protein sequences ... See more keywords
LabCor: Multi-label classification using a label correction strategy
Sign Up to like & getrecommendations! Published in 2021 at "Applied Intelligence"
DOI: 10.1007/s10489-021-02674-y
Abstract: Multi-label classification is a branch of machine learning that can effectively reflect real-world problems. Among all the multi-label classification methods, stacked binary relevance (2BR) is a classic approach. Based on 2BR, a series of optimized… read more here.
Keywords: label; two level; classification; multi label ... See more keywords
Learning safe multi-label prediction for weakly labeled data
Sign Up to like & getrecommendations! Published in 2017 at "Machine Learning"
DOI: 10.1007/s10994-017-5675-z
Abstract: In this paper we study multi-label learning with weakly labeled data, i.e., labels of training examples are incomplete, which commonly occurs in real applications, e.g., image classification, document categorization. This setting includes, e.g., (i) semi-supervised… read more here.
Keywords: label; weakly labeled; multi label; label learning ... See more keywords
Data scarcity, robustness and extreme multi-label classification
Sign Up to like & getrecommendations! Published in 2019 at "Machine Learning"
DOI: 10.1007/s10994-019-05791-5
Abstract: The goal in extreme multi-label classification (XMC) is to learn a classifier which can assign a small subset of relevant labels to an instance from an extremely large set of target labels. The distribution of… read more here.
Keywords: label; classification; extreme multi; multi label ... See more keywords
Semi-supervised dual low-rank feature mapping for multi-label image annotation
Sign Up to like & getrecommendations! Published in 2018 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-018-5719-9
Abstract: Automatic image annotation as a typical multi-label learning problem, has gained extensive attention in recent years owing to its application in image semantic understanding and relevant disciplines. Nevertheless, existing annotation methods share the same challenge… read more here.
Keywords: label; image; multi label; matrix ... See more keywords