分类器集成,其实就是集成学习,通过构建并结合多个学习器来完成学习任务。一般结构是:先产生一组“个体学习器”,再用某种策略将它们结合起来。结合策略主要有平均法、投票法和学习法等。
...移补偿;分类器集成;动态加权 [gap=1021]Keywords: MEMS Gas Sensor; Sensor Array; Drift Compensation; Classifier Ensemble; Dynamic Weights ...
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Multiple classifiers combination method is composed of cascade connection and parallel connection, a deep research about two methods is presented. At first, classifiers ensemble method based on adaptive distance metric via Bagging technique is proposed.
多分类器组合主要分为并联与级联两种方法,本文对多分类器组合的这两种方法进行研究,首先应用Bagging技术,将本文设计的基于自适应距离度量的分类器进行集成(并联组合),提出了一种基于自适应距离度量的最小距离分类器集成方法。
参考来源 - 分类器设计及组合技术研究The techniques of mis-recognition model and multiple classifier combination are proposed and used in the system.
在车牌字符识别中引入了误识模型和多分类器集成技术。
参考来源 - 汉字识别方法研究及其在车牌识别系统中的应用Based on the theoretical results of classifier ensemble, a selective ensemble algorithm is developed based on a strategy of forward greedy selection and post-pruning. The experiments show the proposed algorithm can get a compact and effective classification system.
基于选择性多分类器集成的研究成果,本文提出有选择地集成部分约简训练的分类器构造多分类器系统,并且设计了前向贪心选择和后剪枝的分类器选择策略,试验表明该方法能够获得相对紧凑并且分类能力很强的多分类器系统。
参考来源 - 混合数据知识发现的粗糙计算模型和算法·2,447,543篇论文数据,部分数据来源于NoteExpress
在此,研究了几种不同的分类器集成方法。
设计了一种基于主成分分析的分类器集成方法。
A classifiers ensemble approach based on Principal Component Analysis (PCA) was proposed.
差异性是提高分类器集成泛化性能的重要因素。
Diversity among base classifiers is known to be an important factor for improving generalization performance in ensemble learning.
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