Results 51 to 60 of about 98,421 (281)

Effect of Balancing Data Using Synthetic Data on the Performance of Machine Learning Classifiers for Intrusion Detection in Computer Networks

IEEE Access, 2022
Attacks on computer networks have increased significantly in recent days, due in part to the availability of sophisticated tools for launching such attacks as well as the thriving underground cyber-crime economy to support it. Over the past several years,
Ayesha Siddiqua Dina, A. B. Siddique, D. Manivannan   +2 more
doaj   +1 more source

Anomaly Detection for imbalanced datasets with Deep Generative Models [PDF]

, 2018
Many important data analysis applications present with severely imbalanced datasets with respect to the target variable. A typical example is medical image analysis, where positive samples are scarce, while performance is commonly estimated against the ...
Buitrago, Nazly Rocio Santos, Mavroeidis, Dimitrios, Menkovski, Vlado, Tonnaer, Loek   +3 more
core   +1 more source

Class Rectification Hard Mining for Imbalanced Deep Learning

, 2017
Recognising detailed facial or clothing attributes in images of people is a challenging task for computer vision, especially when the training data are both in very large scale and extremely imbalanced among different attribute classes.
Dong, Qi, Gong, Shaogang, Zhu, Xiatian
core   +1 more source

RaMBat: Accurate identification of medulloblastoma subtypes from diverse data sources with severe batch effects

Molecular Oncology, EarlyView.
To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

Network divergence analysis identifies adaptive gene modules and two orthogonal vulnerability axes in pancreatic cancer

Molecular Oncology, EarlyView.
Tumors contain diverse cellular states whose behavior is shaped by context‐dependent gene coordination. By comparing gene–gene relationships across biological contexts, we identify adaptive transcriptional modules that reorganize into distinct vulnerability axes.
Brian Nelson, Lyanne Delgado‐Coka, Natalia Marchenko, Luisa F. Escobar‐Hoyos, Kenneth R. Shroyer, Alisa Yurovsky, Trey Ideker, Gábor Balázsi, Thomas MacCarthy, Scott Powers   +9 more
wiley   +1 more source

Regularization for Deep Imbalanced Regression Based on Quantitative Relationship

Big Data Mining and Analytics
Imbalanced datasets are prevalent in real life. The imbalanced datasets pose challenges for classification and regression tasks. Compared to imbalanced classification, imbalanced regression deals with continuous labels. The positional relationship of the
Heng Zhao, Jiehao Chen, Xianghua Fu
doaj   +1 more source

Evolutionary deep belief networks with bootstrap sampling for imbalanced class datasets

IJAIN (International Journal of Advances in Intelligent Informatics), 2019
Imbalanced class data is a common issue faced in classification tasks. Deep Belief Networks (DBN) is a promising deep learning algorithm when learning from complex feature input.
A’inur A’fifah Amri, Amelia Ritahani Ismail, Omar Abdelaziz Mohammad   +2 more
doaj   +1 more source

TGT: A Novel Adversarial Guided Oversampling Technique for Handling Imbalanced Datasets

Egyptian Informatics Journal, 2021
With the volume of data increasing exponentially, there is a growing interest in helping people to benefit from their data regardless of its poor quality.
Ayat Mahmoud, Ayman El-Kilany, Farid Ali, Sherif Mazen   +3 more
doaj   +1 more source

Predictive Modeling of ICU Healthcare-Associated Infections from Imbalanced Data. Using Ensembles and a Clustering-Based Undersampling Approach

, 2019
Early detection of patients vulnerable to infections acquired in the hospital environment is a challenge in current health systems given the impact that such infections have on patient mortality and healthcare costs.
Ballesteros-Herráez, Juan Carlos, Kraiem, Mohamed S., Moreno-García, María N., Sánchez-Barba, Mercedes, Sánchez-Hernández, Fernando   +4 more
core   +1 more source

Deciphering transcriptional plasticity in pancreatic ductal adenocarcinoma reveals alterations in sensory neuron innervation

Molecular Oncology, EarlyView.
Pancreatic sensory neurons innervating healthy and PDAC tissue were retrogradely labeled and profiled by single‐cell RNA sequencing. Tumor‐associated innervation showed a dominant neurofilament‐positive subtype, altered mitochondrial gene signatures, and reduced non‐peptidergic neurons.
Elena Genova, Michele Montrone, Uday Rangaswamy, Francesco Diversi, Irene Schiavo, Denise Ferrarini, Roberta Di Florio, Irene Longo, Michele Coscia, Nicola Zamboni, Giorgia Demontis, Lisa Veghini, Vincenzo Corbo, Remo Sanges, Paul Heppenstall   +14 more
wiley   +1 more source