Zobrazeno 1 - 10
of 124
pro vyhledávání: '"Ganaie, M. A."'
Autor:
Madan, Surbhi, Ghosh, Shreya, Sookha, Lownish Rai, Ganaie, M. A., Subramanian, Ramanathan, Dhall, Abhinav, Gedeon, Tom
Estimating the Most Important Person (MIP) in any social event setup is a challenging problem mainly due to contextual complexity and scarcity of labeled data. Moreover, the causality aspects of MIP estimation are quite subjective and diverse. To thi
Externí odkaz:
http://arxiv.org/abs/2409.06224
Publikováno v:
Neurocomputing, 2024
Generalized eigenvalue proximal support vector machine (GEPSVM) has attracted widespread attention due to its simple architecture, rapid execution, and commendable performance. GEPSVM gives equal significance to all samples, thereby diminishing its r
Externí odkaz:
http://arxiv.org/abs/2408.01713
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems, 2024
The domain of machine learning is confronted with a crucial research area known as class imbalance learning, which presents considerable hurdles in precise classification of minority classes. This issue can result in biased models where the majority
Externí odkaz:
http://arxiv.org/abs/2307.07881
The decision tree ensembles use a single data feature at each node for splitting the data. However, splitting in this manner may fail to capture the geometric properties of the data. Thus, oblique decision trees generate the oblique hyperplane for sp
Externí odkaz:
http://arxiv.org/abs/2304.06788
Autor:
Tanveer, M., Ganaie, M. A., Beheshti, Iman, Goel, Tripti, Ahmad, Nehal, Lai, Kuan-Ting, Huang, Kaizhu, Zhang, Yu-Dong, Del Ser, Javier, Lin, Chin-Teng
Over the years, Machine Learning models have been successfully employed on neuroimaging data for accurately predicting brain age. Deviations from the healthy brain aging pattern are associated to the accelerated brain aging and brain abnormalities. H
Externí odkaz:
http://arxiv.org/abs/2212.03868
Publikováno v:
IEEE Journal of Biomedical Health and Informatics, 2022
Machine learning models have been successfully employed in the diagnosis of Schizophrenia disease. The impact of classification models and the feature selection techniques on the diagnosis of Schizophrenia have not been evaluated. Here, we sought to
Externí odkaz:
http://arxiv.org/abs/2203.11610
Neural networks have been successfully employed in various domains such as classification, regression and clustering, etc. Generally, the back propagation (BP) based iterative approaches are used to train the neural networks, however, it results in t
Externí odkaz:
http://arxiv.org/abs/2203.11316
Publikováno v:
Neural Networks, Elsevier, 2022
Random Forest is an ensemble of decision trees based on the bagging and random subspace concepts. As suggested by Breiman, the strength of unstable learners and the diversity among them are the ensemble models' core strength. In this paper, we propos
Externí odkaz:
http://arxiv.org/abs/2111.02010
Publikováno v:
Annals of Operations Research, Springer (2022) 1-46
Twin support vector machine (TWSVM) and twin support vector regression (TSVR) are newly emerging efficient machine learning techniques which offer promising solutions for classification and regression challenges respectively. TWSVM is based upon the
Externí odkaz:
http://arxiv.org/abs/2105.00336
Publikováno v:
Engineering Applications of Artificial Intelligence, 2022
Ensemble learning combines several individual models to obtain better generalization performance. Currently, deep learning architectures are showing better performance compared to the shallow or traditional models. Deep ensemble learning models combi
Externí odkaz:
http://arxiv.org/abs/2104.02395