Handling Label Noise in Microarray Classification with One-Class Classifier Ensemble
2015The advance of high-throughput techniques, such as gene microarrays and protein chips have a major impact on contemporary biology and medicine. Due to the high-dimensionality and complexity of the data, it is impossible to analyze it manually. Therefore machine learning techniques play an important role in dealing with such data.
Bartosz Krawczyk, Michal Wozniak 0001
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Process Controls in Classifying, Handling, Storing and Baking Devices and PWBs
On-Demand Webinars, 2009ABSTRACT The handling, transportation, storage and packaging of Devices and PWBs has become critical as the industry has migrated to higher temperature lead free assembly processes. Devices have expanded beyond the traditional SMD ICs and now includes any non-IC device that will likely be subjected to the higher temperature lead free (
Steven Martell, Mumtaz Bora
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A Responsible AI approach for designing resilient classifier to handle incomplete data
Intelligent Data Analysis: An International JournalMissing values can greatly affect analyses and decision-making in many fields. In the context of Responsible Artificial Intelligence (AI), ensuring the robustness of machine learning models is essential because Responsible AI emphasizes reliability and interpretability in decision-making processes.
Sairam Utukuru, P. Radha Krishna 0001
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Detecting, Classifying, and Handling Contradictions in a Large, Dynamic Information Environment
2006Abstract : A new approach to perturbation tolerance was identified -- the Meta-Cognitive Loop (MCL) -- for responding to contradictions and other anomalies in complex settings. Further investigations with MCL included identifying architectural requirements, and applying MCL to various domains including reinforcement learning, common-sense reasoning ...
Scott Fults +4 more
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Probabilistic Diagnostic Model for Handling Classifier Degradation in Machine Learning
2019Several studies point out different causes of performance degradation in supervised machine learning. Problems such as class imbalance, overlapping, small-disjuncts, noisy labels, and sparseness limit accuracy in classification algorithms. Even though a number of approaches either in the form of a methodology or an algorithm try to minimize performance
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Handling Data Imbalance Using Text Augmentation For Classifying Public Complaints
2023 International Conference on Computer, Control, Informatics and its Applications (IC3INA), 2023Muhammad Rizqi Indrahimawan +2 more
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Handling Missing Values Based on Similarity Classifiers and Fuzzy Entropy Measures
Electronics (Switzerland), 2022Samih M Mostafa +2 more
exaly
Classifying Complaint Reports Using RNN and Handling Imbalanced Dataset
2022 9th International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE), 2022Oktefvia Aruda Lisjana +1 more
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A New Combination of Diversity Techniques in Ensemble Classifiers for Handling Complex Concept Drift
Studies in Big Data, 2019Moamar Sayed-Mouchaweh +2 more
exaly