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Results for classification performance

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24 papers · ranked by Valyu relevance

01
AarXiv15 Apr 2026
Evaluating Supervised Machine Learning Models: Principles, Pitfalls, and Metric Selection
Xuanyan Liu, Ignacio Cabrera Martin, Marcello Trovati, Xiaolong Xu + 1 more
The evaluation of supervised machine learning models is a critical stage in the development of reliable predictive systems. Despite the widespread availability of machine learning libraries and automated workflows, model assessment is often reduced to the reporting of a small set of aggregate metrics, which can lead to…
90relevance
02
BbioRxiv4 Nov 2025
Deep Blueprint: A Literature Review and Guide to Automated Image Classification for Ecologists
Chloe A. Game, Nils Piechaud, Kerry L. Howell
Deep learning (DL) is a powerful tool to extract ecological information from large image datasets efficiently and consistently. However, applying these methods remains challenging, due in part to the complexity of DL workflows and the dynamic nature of available tools. To address this, we created a practical guide and…
89relevance
03
PPubMed21 Oct 2025
Intelligent Dental Handpiece: Real-Time Motion Analysis for Skill Development
Mohamed Sallam, Yousef Salah, Yousef Osman, Ali Hegazy + 4 more
Modern dental education increasingly calls for smarter tools that combine precision with meaningful feedback. In response, this study presents the Intelligent Dental Handpiece (IDH), a next-generation training tool designed to support dental students and professionals by providing real-time insights into their…
87relevance
04
PPubMed16 Dec 2025
Malaria Parasite Cell Classification Using Transfer Learning with State-of-the-Art CNN Architectures
Azhar Ali Laghari, Wazir Muhammad, Mudasar Latif Memon, Ayaz Hussain + 2 more
Title: Simple Summary Malaria is a fatal disease caused by parasites transmitted via mosquito bites, and precise diagnosis is essential for efficient treatment. However, conventional diagnostic techniques, such as microscopy, are labor-intensive and require skilled staff, usually resulting in treatment delays. This…
87relevance
05
CchemRxiv23 Dec 2025
Predicting Sequence Dependent Fluorescence with Classic Machine Learning Models
Authors not listed
Terminally labeled DNA oligonucleotides have wide applications in modern biology and biotechnological applications. It has been observed that the fluorescent intensity of light released from these fluorescent labels is heavily influenced by the terminal sequence of nucleotides. Recent studies have assayed and published…
84relevance
06
PPubMed11 Dec 2025
A multidimensional analysis of the 21 st century competencies scale through ai-driven data mining techniques
Nigmet Koklu
In recent years, evaluating competencies such as knowledge, practical skills, character traits, and meta-learning capabilities has gained increasing importance in educational research. As educational datasets grow larger and more complex, machine learning offers promising tools for analyzing student responses and…
84relevance
07
AarXiv2 Feb 2026
Malware Detection Through Memory Analysis
Sarah Nassar
—This paper summarizes the research conducted for a malware detection project using the Canadian Institute for Cybersecurity's MalMemAnalysis-2022 dataset. The purpose of the project was to explore the effectiveness and efficiency of machine learning techniques for the task of binary classification (i.e., benign or…
84relevance
08
AarXiv4 Jul 2026
A Unified Algebraic Framework for Classification Performance Evaluation
Ronaldo C. Prati
We propose a unified algebraic framework for classification performance evaluation that encompasses binary, multiclass, multilabel, ordinal, hierarchical, cost-sensitive, and soft-label settings within a single formalism. The foundation is a representation of actual and predicted labels as binary indicator matrices…
83relevance
09
PPubMed11 Dec 2025
Medical pattern classification using a novel binary similarity approach based on an associative classifier
Osvaldo Velazquez-Gonzalez, Antonio Alarcón-Paredes, Cornelio Yañez-Marquez
Classification is a central task in machine learning, underpinning applications in domains such as finance, medicine, engineering, information technology, and biology. However, machine learning pattern classification can become a complex or even inexplicable task for current robust models due to the complexity of…
82relevance
10
PPubMed5 Feb 2026
Addressing Class Imbalance in Fetal Health Classification: Rigorous Benchmarking of Multi-Class Resampling Methods on Cardiotocography Data
Zainab Subhi Mahmood Hawrami, Mehmet Ali Cengiz, Emre Dünder, Ioannis Tsakiridis
Background/Objectives: Fetal health is essential in prenatal care, influencing both maternal and fetal outcomes. Cardiotocography (CTG) monitors uterine contractions and fetal heart rate, yet manual interpretation exhibits significant inter-examiner variability. Machine learning offers automated alternatives; however…
82relevance
11
CchemRxiv6 Jan 2026
Embedding-Based Applicability Domain for Graph Neural Networks: A Comprehensive Benchmark on Molecular Property Prediction
Authors not listed
Graph Neural Networks (GNNs) are powerful tools for molecular property prediction, but they are not magic. When applied to molecules unlike their training data, they produce unreliable predictions that are difficult to detect. The Applicability Domain (AD) concept addresses this by defining regions of chemical space…
81relevance
12
CchemRxiv17 Dec 2025
Multi-Reactor Batch Scheduling Strategies for Pharmaceutical Production Under Uncertainty: A Comparative Statistical and Machine Learning Analysis
Authors not listed
Background: Pharmaceutical batch scheduling in multi-reactor configurations presents complex optimization challenges under operational uncertainty, yet limited research addresses how parallel processing capacity affects heuristic performance and predictive modeling. Objectives: This study investigated scheduling…
81relevance
13
PPubMed30 Dec 2025
XcepFusion for brain tumor detection using a hybrid transfer learning framework with layer pruning and freezing
Deependra Rastogi, Prashant Johri, Seifedine Kadry, SeongKi Kim + 3 more
For effective treatment options and better patient outcomes, early and accurate diagnosis of brain tumors is essential. This research introduces an innovative strategy to improving brain tumor diagnosis accuracy by combining deep learning with traditional machine learning classifiers. This research investigation…
81relevance
14
PPubMed21 Apr 2026
An Effective Model-Based Voting Classifier for Diabetes Mellitus Classification
Diyar Qader Zeebaree, Merdin Shamal Salih, Danial William Odeesho, Dilovan Asaad Zebari + 5 more
Diabetes mellitus is a health issue that is rapidly increasing worldwide, and it affects more than 347 million people globally. It is important to note that the disease can be successfully detected in its early stages, enabling physicians to avoid complications and improve patient outcomes. Despite the fact that…
80relevance
15
BbioRxiv25 Aug 2026
Artificial intelligence model: optimizing cancer risk level predictions using machine learning and deep learning approaches
Areen Arabiat, Hamza Abu Owida, Suhaila Abuowaida, Nawaf Alshdaifat + 2 more
This study emphasizes the potential of computational techniques in cancer risk assessment, highlighting opportunities for specific and data-driven healthcare solutions. It examines the use of artificial intelligence (AI), machine learning (ML), and deep learning (DL) approaches to improve cancer risk assessment using a…
79relevance
16
AarXiv15 Nov 2025
Evaluation of Multi- and Single-objective Learning Algorithms for Imbalanced Data
Szymon Wojciechowski, Michał Woźniak
Many machine learning tasks aim to find models that work well not for a single, but for a group of criteria, often opposing ones. One such example is imbalanced data classification, where, on the one hand, we want to achieve the best possible classification quality for data from the minority class without degrading the…
76relevance
17
BbioRxiv14 Jan 2026
Hybrid TF-IDF and SBERT Feature Engineering with SMOTE-Tomek Resampling for Enhanced Software Requirements Classification
Hashim Ali, Raja Sarath Kumar Boddu, Umer Tanveer, Aamir Saeed + 4 more
Software requirements classification remains one of the important challenges in requirements engineering. Engineering that affects the smoothness of project success about software development life cycles. in this paper, a novel hybrid solution is being presented that beats the benchmarks set by previous approaches…
76relevance
18
PPubMed19 Mar 2026
Novel Sewer Defect Prediction Leveraging Advanced Machine Learning (ML) Models
Vannary Seng, Barbara J. Lence, Sudhir Kshirsagar, Srujana Rangapuram + 1 more
A novel approach to sewer network assessment is presented that uses artificial intelligence (AI)/machine learning (ML) to predict infiltration and structural defect occurrences in each pipe instead of estimating the traditional criteria-based overall pipe condition or likelihood of failure. A comparative analysis of…
76relevance
19
AarXiv5 Jun 2026
SleepExplain: Explainable Non-Rapid Eye Movement and Rapid Eye Movement Sleep Stage Classification from EEG Signal
Rafsan Jany, Md. Hamjajul Ashmafee, Iqram Hussain, Md Azam Hossain
Classification of sleep stages is one of the most important diagnostic approaches for a variety of sleep-related disorders. Electroencephalography (EEG) is regarded as a powerful tool for examining the association between neurological effects and sleep phases since it correctly identifies sleep-related neurological…
75relevance
20
AarXiv24 May 2026
On the Impact of Class Imbalance on the Learning Dynamics of Deep Neural Networks:An Intuitive Insight
Ismail B. Mustapha, Shafaatunnur Hasan, Sunday O. Olatunji, Hatem S. Y. Nabus
Class imbalance in deep neural networks (DNNs) has witnessed a rapid increase in research attention in recent years. However, the varying accounts of the reasons behind the poor performance of DNN on imbalance data in pertinent literature shows that little is known about how this agelong phenomenon impacts the…
71relevance
21
BbioRxiv30 Jun 2026
Impacts of batch effects on the performance of machine learning classifiers across multiple studies
Preston Raab, W. Evan Johnson, Stephen R. Piccolo
Precision medicine relies on accurate and generalizable predictions for patients across the spectrum of human diversity. Because capturing biological heterogeneity requires large sample sizes, researchers must often aggregate data from several experimental batches or independent studies. This integration allows for…
70relevance
22
CchemRxiv15 Oct 2025
DeepChem-DEL: An Open Source Framework for Reproducible DEL Modeling and Benchmarking
Authors not listed
DNA-encoded libraries (DELs) have emerged as a powerful platform for screening ultra-large chemical spaces by leveraging DNA barcodes to tag and track individual small molecules. Recent work has shown that machine learning can enhance DEL based hit discovery by denoising sequencing artifacts and improving binder…
70relevance
23
CchemRxiv8 Oct 2025
End-to-end integration of Density Functional Theory simulations and Machine Learning affords broad feasibility model for Nickel metallaphotoredox Csp2-Csp3 cross-coupling reactions
Authors not listed
Nickel/photoredox catalysis in cross-coupling reactions has recently emerged as a powerful tool for efficient C–C bond formation as it enables mild operating conditions, thus expanding synthetic scope to molecules of pharmaceutical interest. Successful routine implementation of such reactions is limited, due to the…
69relevance
24
BbioRxiv15 Apr 2026
Classification of Healthy People and Schizophrenics Using Time- Frequency Domain Features Extracted from Electroencephalogram Signals
Nazila Ahmadi Daryakenari, Seyed Kamaleddin Setaredan
Schizophrenia (SZ) is a chronic and complex mental disorder associated with neurobiological deficits. The complexity and heterogeneity of schizophrenia symptoms pose challenges for objective diagnosis, which is currently based on behavioral and clinical manifestations. Furthermore, other psychiatric disorders such as…
65relevance

Results for classification performance

Evaluating Supervised Machine Learning Models: Principles, Pitfalls, and Metric Selection

Deep Blueprint: A Literature Review and Guide to Automated Image Classification for Ecologists

Intelligent Dental Handpiece: Real-Time Motion Analysis for Skill Development

Malaria Parasite Cell Classification Using Transfer Learning with State-of-the-Art CNN Architectures

Predicting Sequence Dependent Fluorescence with Classic Machine Learning Models

A multidimensional analysis of the 21 st century competencies scale through ai-driven data mining techniques

Malware Detection Through Memory Analysis

A Unified Algebraic Framework for Classification Performance Evaluation

Medical pattern classification using a novel binary similarity approach based on an associative classifier

Addressing Class Imbalance in Fetal Health Classification: Rigorous Benchmarking of Multi-Class Resampling Methods on Cardiotocography Data

Embedding-Based Applicability Domain for Graph Neural Networks: A Comprehensive Benchmark on Molecular Property Prediction

Multi-Reactor Batch Scheduling Strategies for Pharmaceutical Production Under Uncertainty: A Comparative Statistical and Machine Learning Analysis

XcepFusion for brain tumor detection using a hybrid transfer learning framework with layer pruning and freezing

An Effective Model-Based Voting Classifier for Diabetes Mellitus Classification

Artificial intelligence model: optimizing cancer risk level predictions using machine learning and deep learning approaches

Evaluation of Multi- and Single-objective Learning Algorithms for Imbalanced Data

Hybrid TF-IDF and SBERT Feature Engineering with SMOTE-Tomek Resampling for Enhanced Software Requirements Classification

Novel Sewer Defect Prediction Leveraging Advanced Machine Learning (ML) Models

SleepExplain: Explainable Non-Rapid Eye Movement and Rapid Eye Movement Sleep Stage Classification from EEG Signal

On the Impact of Class Imbalance on the Learning Dynamics of Deep Neural Networks:An Intuitive Insight

Impacts of batch effects on the performance of machine learning classifiers across multiple studies

DeepChem-DEL: An Open Source Framework for Reproducible DEL Modeling and Benchmarking

End-to-end integration of Density Functional Theory simulations and Machine Learning affords broad feasibility model for Nickel metallaphotoredox Csp2-Csp3 cross-coupling reactions

Classification of Healthy People and Schizophrenics Using Time- Frequency Domain Features Extracted from Electroencephalogram Signals

Evaluating Supervised Machine Learning Models: Principles, Pitfalls, and Metric Selection

Deep Blueprint: A Literature Review and Guide to Automated Image Classification for Ecologists

Intelligent Dental Handpiece: Real-Time Motion Analysis for Skill Development

Malaria Parasite Cell Classification Using Transfer Learning with State-of-the-Art CNN Architectures

Predicting Sequence Dependent Fluorescence with Classic Machine Learning Models

A multidimensional analysis of the 21 st century competencies scale through ai-driven data mining techniques

Malware Detection Through Memory Analysis

A Unified Algebraic Framework for Classification Performance Evaluation

Medical pattern classification using a novel binary similarity approach based on an associative classifier

Addressing Class Imbalance in Fetal Health Classification: Rigorous Benchmarking of Multi-Class Resampling Methods on Cardiotocography Data

Embedding-Based Applicability Domain for Graph Neural Networks: A Comprehensive Benchmark on Molecular Property Prediction

Multi-Reactor Batch Scheduling Strategies for Pharmaceutical Production Under Uncertainty: A Comparative Statistical and Machine Learning Analysis

XcepFusion for brain tumor detection using a hybrid transfer learning framework with layer pruning and freezing

An Effective Model-Based Voting Classifier for Diabetes Mellitus Classification

Artificial intelligence model: optimizing cancer risk level predictions using machine learning and deep learning approaches

Evaluation of Multi- and Single-objective Learning Algorithms for Imbalanced Data

Hybrid TF-IDF and SBERT Feature Engineering with SMOTE-Tomek Resampling for Enhanced Software Requirements Classification

Novel Sewer Defect Prediction Leveraging Advanced Machine Learning (ML) Models

SleepExplain: Explainable Non-Rapid Eye Movement and Rapid Eye Movement Sleep Stage Classification from EEG Signal

On the Impact of Class Imbalance on the Learning Dynamics of Deep Neural Networks:An Intuitive Insight

Impacts of batch effects on the performance of machine learning classifiers across multiple studies

DeepChem-DEL: An Open Source Framework for Reproducible DEL Modeling and Benchmarking

End-to-end integration of Density Functional Theory simulations and Machine Learning affords broad feasibility model for Nickel metallaphotoredox Csp2-Csp3 cross-coupling reactions

Classification of Healthy People and Schizophrenics Using Time- Frequency Domain Features Extracted from Electroencephalogram Signals