☆ 4.7 Article

An AUC-maximizing classifier for skewed and partially labeled data with an application in clinical prediction modeling

KNOWLEDGE-BASED SYSTEMS (2023)

相关参考文献

注意：仅列出部分参考文献，下载原文获取全部文献信息。

Article Computer Science, Artificial Intelligence

TSK fuzzy system fusion at sensitivity-ensemble-level for imbalanced data classification

Yuanpeng Zhang et al.

Summary: This study proposes a novel interpretable sensitivity-ensemble-level TSK-fuzzy system (ISE-TSK-FS) to achieve both promising classification performance and reasonable interpretability on imbalanced datasets. The study uses objective sensitivity based on 0-order Takagi-Sugeno-Kang Fuzzy System (0-TSK-FS) to detect informative objects and selects them iteratively using clustering and undersampling. A self-paced factor is introduced to avoid overfitting. Experimental results on synthetic, UCI, and medical datasets demonstrate the promising performance and interpretability of ISE-TSK-FS on imbalanced data.

INFORMATION FUSION (2023)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Adversarially Robust One-Class Novelty Detection

Shao-Yuan Lo et al.

Summary: In this article, the vulnerability of deep novelty detectors to adversarial examples is studied, and it is found that existing novelty detectors are susceptible to adversarial attacks and commonly-used defense approaches for classification tasks have limited effectiveness in one-class novelty detection. Therefore, a defense strategy, called PrincipaLS, is proposed to improve the robustness against adversarial examples in novelty detection.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2023)

添加到收藏夹

Article Respiratory System

An artificial intelligence approach for predicting death or organ failure after hospitalization for COVID-19: development of a novel risk prediction tool and comparisons with ISARIC-4C, CURB-65, qSOFA, and MEWS scoring systems

Stephen Wai Hang Kwok et al.

Summary: This study developed a risk prediction tool using machine learning algorithms for COVID-19 patients and compared it with existing risk scores. The new model showed improved performance in predicting composite outcomes and may have utility in clinical practice.

RESPIRATORY RESEARCH (2023)

添加到收藏夹

Article Automation & Control Systems

A Deep-Ensemble-Level-Based Interpretable Takagi-Sugeno-Kang Fuzzy Classifier for Imbalanced Data

Guanjin Wang et al.

Summary: In this study, a novel deep-ensemble-level-based TSK fuzzy classifier is proposed for imbalanced data classification tasks. By stacking zero-order TSK fuzzy subclassifiers on the minority class and its problematic areas in the deep ensemble, promising classification performance and high interpretability are achieved.

IEEE TRANSACTIONS ON CYBERNETICS (2022)

添加到收藏夹

Article Computer Science, Artificial Intelligence

An accuracy-maximization learning framework for supervised and semi-supervised imbalanced data

Guanjin Wang et al.

Summary: In this paper, a new concept of accuracy maximization for randomized learning methods on imbalanced datasets is proposed. The accuracy-maximization learning framework is developed and applied to Extreme Learning Machine (ELM), resulting in a new accuracy-maximization extreme learning machine (AMELM). Experimental results show that AMELM achieves satisfactory performances on labeled or partially labeled imbalanced data, demonstrating its potential for practical applications.

KNOWLEDGE-BASED SYSTEMS (2022)

添加到收藏夹

Article Computer Science, Theory & Methods

The use of generative adversarial networks to alleviate class imbalance in tabular data: a survey

Rick Sauber-Cole et al.

Summary: The existence of class imbalance in a dataset can bias the classifier towards majority classification. Generative Adversarial Networks (GANs) have been used to generate instances of the underrepresented class(es) to mitigate this issue. While most research focuses on their application in computer vision tasks, GANs are also being used for tabular data with traditional structured data types.

JOURNAL OF BIG DATA (2022)

添加到收藏夹

Article Computer Science, Information Systems

The harm of class imbalance corrections for risk prediction models: illustration and simulation using logistic regression

Ruben van den Goorbergh et al.

Summary: This study examined the effect of correcting class imbalance on the performance of logistic regression models and found that methods such as random undersampling, random oversampling, and SMOTE did not improve model performance and resulted in poorly calibrated models. Imbalance correction did not enhance the ability of the models to distinguish between patients with and without the outcome event.

JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION (2022)

添加到收藏夹

Article Automation & Control Systems

AUC-Based Extreme Learning Machines for Supervised and Semi-Supervised Imbalanced Classification

Guanjin Wang et al.

Summary: In this article, AUC-ELM and SAUC-ELM models were proposed to address imbalanced binary classification tasks by integrating AUC maximization into the ELM framework. These two models showed superior performance in classification and training speed compared to other methods in experiments.

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Intuitionistic fuzzy proximal support vector machine for multicategory classification problems

Scindhiya Laxmi et al.

Summary: Intuitionistic fuzzy-based support vector machine is an effective method for multi-category classification problems, which assigns fuzzy score functions to each training point to significantly reduce the impacts of noises and outliers in the dataset.

SOFT COMPUTING (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence

A survey on semi-supervised learning

Jesper E. Van Engelen et al.

MACHINE LEARNING (2020)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Laplacian least learning machine with dynamic updating for imbalanced classification

Jie Zhou et al.

APPLIED SOFT COMPUTING (2020)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Least squares support vector machines with fast leave-one-out AUC optimization on imbalanced prostate cancer data

Guanjin Wang et al.

INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS (2020)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Optimal scale selection by integrating uncertainty and cost-sensitive learning in multi-scale decision tables

Xueqiu Zhang et al.

INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS (2020)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Multi-view semi-supervised least squares twin support vector machines with manifold-preserving graph reduction

Xijiong Xie

INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS (2020)

添加到收藏夹

Article Computer Science, Artificial Intelligence

General multi -view semi -supervised least squares support vector machines with multi -manifold regularization

Xijiong Xie et al.

INFORMATION FUSION (2020)

添加到收藏夹

Article Business, Finance

A novel dual-weighted fuzzy proximal support vector machine with application to credit risk analysis

Lean Yu et al.

INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS (2020)

添加到收藏夹

Article Computer Science, Information Systems

Auxiliary Classifier Generative Adversarial Network With Soft Labels in Imbalanced Acoustic Event Detection

Xianjun Xia et al.

IEEE TRANSACTIONS ON MULTIMEDIA (2019)

添加到收藏夹

Article Computer Science, Information Systems

An Analytical Framework for TJR Readmission Prediction and Cost-Effective Intervention

Hyo Kyung Lee et al.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2019)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Classification of Imbalanced Data by Oversampling in Kernel Space of Support Vector Machines

Josey Mathew et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2018)

添加到收藏夹

Article Statistics & Probability

Proximal support vector machine techniques on medical prediction outcome

Krystallenia Drosou et al.

JOURNAL OF APPLIED STATISTICS (2017)

添加到收藏夹

Article Computer Science, Artificial Intelligence

A Survey on semi-supervised feature selection methods

Razieh Sheikhpour et al.

PATTERN RECOGNITION (2017)

添加到收藏夹

Article Chemistry, Analytical

Feature selection and analysis on correlated gas sensor data with recursive feature elimination

Ke Yan et al.

SENSORS AND ACTUATORS B-CHEMICAL (2015)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Self-labeled techniques for semi-supervised learning: taxonomy, software and empirical study

Isaac Triguero et al.

KNOWLEDGE AND INFORMATION SYSTEMS (2015)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Manifold proximal support vector machine for semi-supervised classification

Wei-Jie Chen et al.

APPLIED INTELLIGENCE (2014)

添加到收藏夹

Article Computer Science, Information Systems

Tackling the problem of classification with noisy data using Multiple Classifier Systems: Analysis of the performance and robustness

Jose A. Saez et al.

INFORMATION SCIENCES (2013)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Dynamic class imbalance learning for incremental LPSVM

Shaoning Pang et al.

NEURAL NETWORKS (2013)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Inverse matrix-free incremental proximal support vector machine

Zhenfeng Zhu et al.

DECISION SUPPORT SYSTEMS (2012)

添加到收藏夹

Article Computer Science, Artificial Intelligence

KPCA plus LDA: A complete kernel fisher discriminant framework for feature extraction and recognition

J Yang et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2005)

添加到收藏夹

© Peeref 2019-2024. All rights reserved.