CN102184422B - 一种平均错分代价最小化的分类器集成方法 - Google Patents
一种平均错分代价最小化的分类器集成方法 Download PDFInfo
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数据集 | 样本数 | 样本属性数 | 1类样本数 | 2类样本数 | 3类样本数 | 训练集∶测试集 |
Random data | 178 | 24 | 59 | 71 | 48 | 6∶4 |
Wine | 178 | 14 | 59 | 71 | 48 | 6∶4 |
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CN102945255B (zh) * | 2012-10-18 | 2016-06-22 | 浙江大学 | 跨媒体多视角非完美标签学习方法 |
CN103049759B (zh) * | 2012-12-14 | 2015-11-18 | 上海邮政科学研究院 | 一种用于邮政分拣***的邮政编码识别方法 |
CN104573709B (zh) * | 2014-12-24 | 2018-08-03 | 深圳信息职业技术学院 | 基于设置总的错分率的可控置信机器算法 |
CN105320967A (zh) * | 2015-11-04 | 2016-02-10 | 中科院成都信息技术股份有限公司 | 基于标签相关性的多标签AdaBoost集成方法 |
CN108664924B (zh) * | 2018-05-10 | 2022-07-08 | 东南大学 | 一种基于卷积神经网络的多标签物体识别方法 |
CN111181939B (zh) * | 2019-12-20 | 2022-02-25 | 广东工业大学 | 一种基于集成学习的网络入侵检测方法及装置 |
CN112668786B (zh) * | 2020-12-30 | 2023-09-26 | 国能信息技术有限公司 | 一种矿车车辆安全评估预测方法、终端设备和存储介质 |
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Title |
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付忠良等.《分类器动态组合及基于分类器组合的集成学习算法》.《四川大学学报( 工程科学版)》.2011,第43卷(第2期), * |
赵向辉等.《面向目标的带先验概率的AdaBoost 算法》.《四川大学学报( 工程科学版)》.2010,第42卷(第2期), * |
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