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Towards exploiting linear regression for multi-class/multi-label classification: an empirical analysis
Regression and classification are the two main learning tasks in supervised learning, and both of them can be solved by learning a hyperplane from...
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Class-structure preserving multi-view correlated discriminant analysis for multiblock data
With the rapid development in data acquisition methods, multiple data sources are now becoming available to explain different views of an object....
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Global-local information based oversampling for multi-class imbalanced data
Multi-class imbalanced classification is a challenging problem in the field of machine learning. Many methods have been proposed to deal with it, and...
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RETRACTED ARTICLE: Evaluation of image segmentation and multi class object recognition algorithm based on machine learning
This paper mainly updates the image segmentation and multi-target recognition algorithm through the support vector machine algorithm in ML, and...
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Multi-class Concrete Defect Detection Algorithm Based on Rep-PVT
Concrete defects are usually overlapped by multiple defects, making accurate identifying of multi-class defects still a challenging task. In this...
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A meta-learning network method for few-shot multi-class classification problems with numerical data
The support vector machine (SVM) method is an important basis of the current popular multi-class classification (MCC) methods and requires a...
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Generative replay for multi-class modeling of human activities via sensor data from in-home robotic companion pets
Deploying socially assistive robots (SARs) at home, such as robotic companion pets, can be useful for tracking behavioral and health-related changes...
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BD2EMNET: An Innovative Strategy for Managing Multi-class Classification and Class Imbalance Issues in Alzheimer’s Disease
Alzheimer’s Disease (AD) stands as a progressive neurodegenerative ailment that significantly affects the well-being of those afflicted and their...
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Adaptive Containment Control for a Class of Uncertain Multi-agent Systems With Unknown Virtual Control Gain Functions
In this paper, we consider a containment control problem for a class of uncertain multi-agent systems (MASs). The systems contain unknown parameters...
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Multi-class feature selection via Sparse Softmax with a discriminative regularization
Feature selection plays a critical role in many machine learning applications as it effectively addresses the challenges posed by “the curse of...
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VMD-Based Ensembled SMOTEBoost for Imbalanced Multi-class Rotor Mass Imbalance Fault Detection and Diagnosis Under Industrial Noise
PurposeThe purpose of this study is to investigate rotor imbalance fault diagnosis for multi-class imbalanced noisy data in rotor-bearing systems....
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Object Classification Using ECOC Multi-class SVM and HOG Characteristics
Nowadays classification of images into labeled multi-classes is one of the major research problems. In the field of artificial intelligence, the...
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An Independent Constructive Multi-class Classification Algorithm for Predicting the Risk Level of Stress Using Multi-modal Data
Currently, stress is being a root cause for many health issues, and the necessity of identifying the risk level of stress becomes crucial, which can...
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Performance Evaluation of K-SVCR in Multi-class Scenario
The support vector classification regression machine for K-class classification (K-SVCR) based on the “1-verses-1-verses-rest” structure is a unique...
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Overcoming the Challenges in Multi-class Context-Based Sentiment Analysis
Sentiment analysis has been extensively utilized during the past ten years in a variety of fields, including business, social networking, education,...
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Ramp loss KNN-weighted multi-class twin support vector machine
The K-nearest neighbor-weighted multi-class twin support vector machine (KWMTSVM) is an effective multi-classification algorithm which utilizes the...
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Building hierarchical class structures for extreme multi-class learning
Class hierarchical structures play a significant role in large and complex tasks of machine learning. Existing studies on the construction of such...
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An Empirical Study of Multi-class Imbalance Learning Algorithms
Real-life data are often imbalanced which represent the major hurdle in classification applications. Despite incremental improvements, gaining from...
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Breaking down health fakes: a hybrid DNN model for multi-class classification on a self-constructed dataset
The proliferation of social media has led to a corresponding increase in online dissemination of health-related information, not all of which is...
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Multi-class hate speech detection in the Norwegian language using FAST-RNN and multilingual fine-tuned transformers
The growth of social networks has provided a platform for individuals with prejudiced views, allowing them to spread hate speech and target others...
