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Learning Under Concept Drift for Regression-A Systematic Literature Review

IEEE access, 2022, Vol.10, p.45410-45429

2022

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MaasPenn Radiomics Reproducibility Score: A Novel Quantitative Measure for Evaluating the Reproducibility of CT-Based Handcrafted Radiomic Features

Cancers, 2022-03, Vol.14 (7), p.1599

2022

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An interval prototype classifier based on a parameterized distance applied to breast thermographic images

Medical & biological engineering & computing, 2017-06, Vol.55 (6), p.873-884

2017

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Kohonen map-wise regression applied to interval data

Knowledge-based systems, 2021-07, Vol.224, p.107091, Article 107091

2021

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Multiclass Segmentation of Breast Tissue and Suspicious Findings: A Simulation-Based Study for the Development of Self-Steering Tomosynthesis

Tomography (Ann Arbor), 2023-06, Vol.9 (3), p.1120-1132

2023

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A two-level Item Response Theory model to evaluate speech synthesis and recognition

Speech communication, 2022-02, Vol.137, p.19-34

2022

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Impact of Tomosynthesis Acquisition on 3D Segmentations of Breast Outline and Adipose/Dense Tissue with AI: A Simulation-Based Study

Tomography (Ann Arbor), 2023-07, Vol.9 (4), p.1303-1314

2023

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Evaluating regression algorithms at the instance level using item response theory

Knowledge-based systems, 2022-03, Vol.240, p.108076, Article 108076

2022

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Classifying breast lesions in Brazilian thermographic images using convolutional neural networks

Neural computing & applications, 2023-09, Vol.35 (26), p.18989-18997

2023

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Sighted particles: improving swarm optimization by making particles aware of their surroundings

Evolutionary intelligence, 2024-04, Vol.17 (2), p.941-954

2024

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A parametrized approach for linear regression of interval data

Knowledge-based systems, 2017-09, Vol.131, p.149-159

2017

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A swarm-trained k-nearest prototypes adaptive classifier with automatic feature selection for interval data

Neural networks, 2016-08, Vol.80, p.19-33

2016

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Classifier calibration: a survey on how to assess and improve predicted class probabilities

Machine learning, 2023-09, Vol.112 (9), p.3211-3260

2023

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Beyond sigmoids: How to obtain well-calibrated probabilities from binary classifiers with beta calibration

Electronic journal of statistics, 2017-01, Vol.11 (2)

2017

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Hybrid methods for fuzzy clustering based on fuzzy c-means and improved particle swarm optimization

Expert systems with applications, 2015-10, Vol.42 (17-18), p.6315-6328

2015

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A Weighted Learning Vector Quantization Approach for Interval Data

Neural Information Processing, p.504-511

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Modelo preditivo para geração de informações gerenciais para empresas patrocinadoras de entidades fechadas de previdência complementar

Perspectivas contemporâneas, 2023-10, Vol.18, p.1-22

2023

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Optimized Learning Vector Quantization Classifier with an Adaptive Euclidean Distance

Artificial Neural Networks – ICANN 2009, p.799-806

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Item Response Theory for Evaluating Regression Algorithms

2020 International Joint Conference on Neural Networks (IJCNN), 2020, p.1-8

2020

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Evaluating Data Representations for Object Recognition During Pick-and-Place Manipulation Tasks

2022 IEEE International Systems Conference (SysCon), 2022, p.1-6

2022

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Explaining Learning Performance with Local Performance Regions and Maximally Relevant Meta-Rules

Intelligent Systems, 2022, Vol.13653, p.550-564

2022

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Automatic Recognition of Units of Measurement in Product Descriptions from Tax Invoices Using Neural Networks

Computational Processing of the Portuguese Language, p.156-165

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A Comparative Study on Concept Drift Detectors for Regression

Intelligent Systems, p.390-405

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Iris-CV: Classifying Iris Flowers Is Not as Easy as You Thought

Intelligent Systems, p.254-264

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Background Check: A General Technique to Build More Reliable and Versatile Classifiers

2016 IEEE 16th International Conference on Data Mining (ICDM), 2016, p.1143-1148

2016

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Learning Under Concept Drift for Regression-A Systematic Literature Review

MaasPenn Radiomics Reproducibility Score: A Novel Quantitative Measure for Evaluating the Reproducibility of CT-Based Handcrafted Radiomic Features

An interval prototype classifier based on a parameterized distance applied to breast thermographic images

Kohonen map-wise regression applied to interval data

Multiclass Segmentation of Breast Tissue and Suspicious Findings: A Simulation-Based Study for the Development of Self-Steering Tomosynthesis

A two-level Item Response Theory model to evaluate speech synthesis and recognition

Impact of Tomosynthesis Acquisition on 3D Segmentations of Breast Outline and Adipose/Dense Tissue with AI: A Simulation-Based Study

Evaluating regression algorithms at the instance level using item response theory

Classifying breast lesions in Brazilian thermographic images using convolutional neural networks

Sighted particles: improving swarm optimization by making particles aware of their surroundings

A parametrized approach for linear regression of interval data

A swarm-trained k-nearest prototypes adaptive classifier with automatic feature selection for interval data

Classifier calibration: a survey on how to assess and improve predicted class probabilities

Beyond sigmoids: How to obtain well-calibrated probabilities from binary classifiers with beta calibration

Hybrid methods for fuzzy clustering based on fuzzy c-means and improved particle swarm optimization

A Weighted Learning Vector Quantization Approach for Interval Data

Modelo preditivo para geração de informações gerenciais para empresas patrocinadoras de entidades fechadas de previdência complementar

Optimized Learning Vector Quantization Classifier with an Adaptive Euclidean Distance

Item Response Theory for Evaluating Regression Algorithms

Evaluating Data Representations for Object Recognition During Pick-and-Place Manipulation Tasks

Explaining Learning Performance with Local Performance Regions and Maximally Relevant Meta-Rules

Automatic Recognition of Units of Measurement in Product Descriptions from Tax Invoices Using Neural Networks

A Comparative Study on Concept Drift Detectors for Regression

Iris-CV: Classifying Iris Flowers Is Not as Easy as You Thought

Background Check: A General Technique to Build More Reliable and Versatile Classifiers

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