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Can Learning Vector Quantization be an Alternative to SVM and Deep Learning? - Recent Trends and Advanced Variants of Learning Vector Quantization for Classification Learning

机译：可以学习矢量量化是SVM和深度学习的替代品吗？ - 近期趋势和学习传感量化的先进变体进行分类学习

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Thomas Villmann; Andrea Bohnsack; Marika Kaden;
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年度 2016
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1. Can Learning Vector Quantization be an Alternative to SVM and Deep Learning? - Recent Trends and Advanced Variants of Learning Vector Quantization for Classification Learning [J] . Thomas Villmann, Andrea Bohnsack, Marika Kaden Journal of Artificial Intelligence and Soft Computing Research . 2016,第1期

机译：学习矢量量化可以替代SVM和深度学习吗？ -分类向量学习向量量化的最新趋势和高级变体
2. Can Learning Vector Quantization be an Alternative to SVM and Deep Learning? - Recent Trends and Advanced Variants of Learning Vector Quantization for Classification Learning [J] . Thomas Villmann, Andrea Bohnsack, Marika Kaden Journal of Artificial Intelligence and Soft Computing Research . 2016,第1期

机译：学习矢量量化可以替代SVM和深度学习吗？ -分类向量学习向量量化的最新趋势和高级变体
3. Border-sensitive learning in generalized learning vector quantization: an alternative to support vector machines [J] . Kaden Marika, Riedel Martin, Hermann Wieland, Soft computing: A fusion of foundations, methodologies and applications . 2015,第9期

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4. Fusion of deep learning architectures, multilayer feedforward networks and learning vector quantizers for deep classification learning [C] . T. Villmann, M. Biehl, A. Villmann, 2017 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization . 2017

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5. Sentiment Classification Using Different Machine Learning Algorithms and Different Word Vectorizer [D] . Cui, Shuyang. 2021

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6. Classification of Incidental Carcinoma of the Prostate Using Learning Vector Quantization and Support Vector Machines [O] . Torsten Mattfeldt, Danilo Trijic, Hans‐Werner Gottfried, 2004

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7. Aspects in Classification Learning - Review of Recent Developments in Learning Vector Quantization [O] . Kaden M., Lange M., Nebel D., 2014

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8. Eddy Current Signature Classification of Steam Generator Tube Defects Using A Learning Vector Quantization Neural Network [R] . 2005

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Can Learning Vector Quantization be an Alternative to SVM and Deep Learning? - Recent Trends and Advanced Variants of Learning Vector Quantization for Classification Learning

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