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Indexing Density Models for Incremental Learning and Anytime Classification on Data Streams

机译：用于数据流上的增量学习和随时分类的索引密度模型

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作者
Seidl Thomas; Assent Ira; Kranen Philipp; Krieger Ralph; Herrmann Jennifer;
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年度 2009
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原文格式 PDF
正文语种 eng
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1. Streaming chunk incremental learning for class-wise data stream classification with fast learning speed and low structural complexity [J] . Prem Junsawang, Suphakant Phimoltares, Chidchanok Lursinsap PLoS One . 2019,第9期

机译：流块累计学习，具有快速学习速度和低结构复杂性的类化数据流分类
2. Incremental semi-supervised Extreme Learning Machine for Mixed data stream classification [J] . Li Qiude, Xiong Qingyu, Ji Shengfen, Expert systems with applications . 2021,第Deca期

机译：用于混合数据流分类的增量半监督极限学习机
3. A fast incremental extreme learning machine algorithm for data streams classification [J] . Xu Shuliang, Wang Junhong Expert Systems with Application . 2016,第deca期

机译：用于数据流分类的快速增量极限学习机算法
4. Indexing density models for incremental learning and anytime classification on data streams [C] . Thomas Seidl, Ira Assent, Philipp Kranen, International Conference on Extending Database Technology . 2009

机译：用于数据流增量学习和随时分类的索引密度模型
5. Efficient Incremental Model Learning on Data Streams [D] . Chen, Xilun. 2019

机译：高效增量模型在数据流上学习
6. Streaming chunk incremental learning for class-wise data stream classification with fast learning speed and low structural complexity [O] . Prem Junsawang, Suphakant Phimoltares, Chidchanok Lursinsap 2012

机译：流式块增量学习，用于以快速的学习速度和较低的结构复杂度对类数据流进行分类
7. Indexing Density Models for Incremental Learning and Anytime Classification on Data Streams [O] . Seidl Thomas, Assent Ira, Kranen Philipp, 2009

机译：用于增量学习的索引密度模型和数据流上的任意时间分类
8. Studies on a Novel Neuro-dynamic Model for Prediction Learning of Fluctuated Data Streams: Beyond Dichotomy between Probabilistic and Deterministic Models. [R] . Tani, J. 2014

机译：一种用于波动数据流预测学习的新型神经动力学模型的研究：超越概率模型和确定性模型的二分法。

Indexing Density Models for Incremental Learning and Anytime Classification on Data Streams

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