A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Filters
Comprehensive Comparative Study of Multi-Label Classification Methods
[article]
2021
arXiv
pre-print
Preserved Fulltext
Other Versions
Multi-label classification (MLC) has recently received increasing interest from the machine learning community. ...
This work provides a comprehensive empirical study of a wide range of MLC methods on a plethora of datasets from various domains. ...
CONCLUSION This works presents the most comprehensive comparative study of MLC methods to date. It presents an in-depth theoretical and empirical analysis of a variety of MLC methods. ...
arXiv:2102.07113v2
fatcat:jtjefamw35fetjtnatmjvjl544
Label Relation Inference for Multi-Label Aerial Image Classification
2019
IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Multi-label aerial image classification is a challenging visual task and obtaining increasing attention recently. ...
Most of the existing methods resort to training independent classifier for each label, while underlying label correlations are not fully exploited while making predictions. ...
Experiments are conducted on the UCM multi-label dataset and comparisons with relevant existing methods are performed for a comprehensive evaluation. ...
doi:10.1109/igarss.2019.8898934
dblp:conf/igarss/HuaMZ19
fatcat:xwo3x2rmdfabpbyyqyie6ky3ee
GML_DT: A Novel Graded Multi-label Decision Tree Classifier
2021
International Journal of Advanced Computer Science and Applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
The goal of Graded Multi-label Classification (GMLC) is to assign a degree of membership or relevance of a class label to each data point. ...
As opposed to multi-label classification tasks which can only predict whether a class label is relevant or not. ...
Graded Multi-label Classifiers Graded multi-label classification [1] was formalized as an extension of multi-label classification [15] [16] , to predict the degrees of relevance of the labels rather ...
doi:10.14569/ijacsa.2021.0121233
fatcat:7hypf6gr2fbi3c2brvtiwhvuxy
Learning Multi-level Region Consistency with Dense Multi-label Networks for Semantic Segmentation
[article]
2017
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
With comprehensive experiments, we show that the dense multi-label can successfully remove the implausible labels and clear the confusion so as to boost the performance of semantic segmentation systems ...
Per-pixel semantic labelling of an image benefits greatly from the ability to consider region consistency both locally and globally. ...
Multi-label classification has also been widely studied. Traditional methods are based on graphical models [20, 16] , while the recent studies benefit more from CNNs [13, 14, 17] . Gong et al. ...
arXiv:1701.07122v1
fatcat:bn74e6p3szg35b5blcsnrrlmqu
Reading Profiles in Multi-Site Data With Missingness
2018
Frontiers in Psychology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Together, the results show how multiple imputation can be applied to the classification of cases with missing data and can increase the integrity of results from multi-site open access datasets. ...
Here we show that reading profiles can be reliably identified based on Random Forest classification of incomplete behavioral datasets, after the missForest method is used to multiply impute missing values ...
by comparing the synthesized expert labels to the Random Forest classifications. ...
doi:10.3389/fpsyg.2018.00644
pmid:29867632
pmcid:PMC5952106
fatcat:cdl24vlh6vgyvhv4m7lq5xjqxi
Distribution-based Label Space Transformation for Multi-label Learning
[article]
2018
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
By defining the distribution based on the similarity of label vectors, a more comprehensive label structure can be captured. ...
The key to successful multi-label learning algorithms lies in the exploration of inter-label correlations, which usually incur great computational cost. ...
compare the performance of these multi-label classification methods. ...
arXiv:1805.05687v1
fatcat:363yumuqizgfll42q2lbjcgm5m
MORONET: Multi-omics Integration via Graph Convolutional Networks for Biomedical Data Classification
[article]
2020
bioRxiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
We present a novel multi-omics integrative method named Multi-Omics gRaph cOnvolutional NETworks (MORONET) for biomedical classification. ...
To fully utilize the advances in omics technologies and achieve a more comprehensive understanding of human diseases, novel computational methods are required for integrative analysis for multiple types ...
Acknowledgements This work was supported by Indiana University Precision Health Initiative and National Institute of Biomedical Imaging and Bioengineering (R01EB025018). ...
doi:10.1101/2020.07.02.184705
fatcat:lemnficphncsxdkayxyruligbm
Learning Multi-level Region Consistency with Dense Multi-label Networks for Semantic Segmentation
2017
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
With comprehensive experiments, we show that the dense multi-label can successfully remove the implausible labels and clear the confusion so as to boost the performance of semantic segmentation systems ...
Per-pixel semantic labelling of an image benefits greatly from the ability to consider region consistency both locally and globally. ...
Multi-label classification has also been widely studied. ...
doi:10.24963/ijcai.2017/377
dblp:conf/ijcai/ShenLS017
fatcat:qydvclos2vg7vdlkpcznk7imna
Examining Swarm Intelligence-based Feature Selection for Multi-Label Classification
2021
Journal of Soft Computing and Data Mining
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Thus, in this paper, we provide a comprehensive review of different swarm intelligence and evolutionary computing methods of feature selection presented for multi-label classification tasks. ...
We then provided the main characteristics of the existing multi-label feature selection techniques and compared them analytically. ...
Acknowledgment The authors would like to acknowledge Duhok Polytechnic University/ Technical College of Informatics-Akre. ...
doi:10.30880/jscdm.2021.02.02.006
fatcat:biacmvnfmfafhanblgijwki2ta
Improving Machine Reading Comprehension with Multi-Task Learning and Self-Training
2022
Mathematics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Therefore, to meet the comprehensive requirements in such application situations, we construct a multi-task fusion training reading comprehension model based on the BERT pre-training model. ...
In the training phase, since our model requires a large amount of labeled training data, which is often expensive to obtain or unavailable in many tasks, we additionally use self-training to generate pseudo-labeled ...
results of three multi-task learning methods. ...
doi:10.3390/math10030310
fatcat:4gc3cwac5bd3tck57pnicdbfse
Effectiveness of Semi-Supervised Learning and Multi-Source Data in Detailed Urban Landuse Mapping with a Few Labeled Samples
2022
Remote Sensing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
This study aims to explore the effectiveness of a semi-supervised classification framework with multi-source data for detailed urban landuse classification with a few labeled samples. ...
Therefore, previous studies on urban landuse classification have often relied on a small size of labeled samples with very uneven spatial distribution. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs14030648
fatcat:xdxqaaz42zbahp4mlbned24oxu
HPSLPred: An Ensemble Multi-label Classifier for Human Protein Subcellular Location Prediction with Imbalanced Source
[article]
2017
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
First, most of the existing techniques are designed to deal with multi-class rather than multi-label classification, which ignores connections between multiple labels. ...
For solving these two issues, we have developed an ensemble multi-label classifier called HPSLPred, which can be applied for multi-label classification with an imbalanced protein source. ...
Acknowledgements The work was supported by the Natural Science Foundation of China (No. 61370010) and the Natural Science Foundation of Fujian Province of China (No.2014J01253). ...
arXiv:1704.05204v1
fatcat:j3dqu23mhfd4zpqivgukrghmqy
Empirical Studies on Multi-label Classification
2006
2006 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'06)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2008; you can also visit the original URL.
The file type is application/pdf.
In this paper, we present a comparative study on various multi-label approaches using both gene and scene data sets. ...
Our experiments demonstrate that the combined method can take the advantages of the single approaches. ...
Methods Description We use six different multi-label classification approaches in our comparative study. ...
doi:10.1109/ictai.2006.55
dblp:conf/ictai/LiZZ06
fatcat:ps7pggc4m5gy5lle67ptrvv2ey
GCN-IA: User Profile Based on Graph Convolutional Network with Implicit Association Labels
[chapter]
2020
Lecture Notes in Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
On four real-world datasets in Weibo, experimental results demonstrate that GCN-IA produces a significant improvement compared with some state-of-the-art methods. ...
Current researches on multi-label user profile either ignore the implicit associations among labels or do not consider the user and label semantic information in the social networks. ...
Classification module makes multi-label classification based on user representations to predict unlabeled user profiles. ...
doi:10.1007/978-3-030-50420-5_26
fatcat:jzzj2bqscreurkw5o7n7jpbrkm
Multi-Label Classification of Fake News on Social-Media
2022
Zenodo
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
remarks and articulations, and to empower them to find the specific wellspring of information that isn't affected by others. ...
Individuals experience passionate feelings for straightforward alluring contents or plans, and thus, they become casualties of it. ...
Our research team concentrated mostly on the problem transformation method of multi-label classification. ...
doi:10.5281/zenodo.6539309
fatcat:7waxw3rryvhcxgrkqxkack6k3e
« Previous
Showing results 1 — 15 out of 147,573 results