...
机译:使用支持向量机为分层植被分类方法生成学习数据
Department of Mathematical Science and Electrical-Electronic-Computer Engineering, Graduate School of Engineering Science, Akita University, 1-1, Tegata Gakuen-machi, Akita-shi, Akita 010-8502, Japan;
Department of Mathematical Science and Electrical-Electronic-Computer Engineering, Graduate School of Engineering Science, Akita University, 1-1, Tegata Gakuen-machi, Akita-shi, Akita 010-8502, Japan;
Department of Mathematical Science and Electrical-Electronic-Computer Engineering, Graduate School of Engineering Science, Akita University, 1-1, Tegata Gakuen-machi, Akita-shi, Akita 010-8502, Japan;
The Open University of Japan, 1-1, Tegata Gakuen-machi, Akita-shi, Akita 010-8502, Japan;
Akita Office of River and National Highway, Tohoku Regional Bureau, Ministry of Land, Infrastructure, Transport and Tourism 1-10-29, Sanno, Akita-shi, Akita 010-0951, Japan;
Akita Office of River and National Highway, Tohoku Regional Bureau, Ministry of Land, Infrastructure, Transport and Tourism 1-10-29, Sanno, Akita-shi, Akita 010-0951, Japan;
Akita Office of River and National Highway, Tohoku Regional Bureau, Ministry of Land, Infrastructure, Transport and Tourism 1-10-29, Sanno, Akita-shi, Akita 010-0951, Japan;
Support vector machine; Learned data; Vegetation classification; River bank;
机译:使用支持向量机为分层植被分类方法生成学习数据
机译:痴呆症预测中的数据挖掘方法:线性判别分析,逻辑回归,神经网络,支持向量机,分类树和随机森林的准确性,敏感性和特异性的真实数据比较
机译:从MODIS数据生成GLASS植被分数覆盖产品的四种机器学习方法的比较
机译:用于轨道数据分类的分层模糊支持向量机(SVM)
机译:使用支持向量机主动学习硬皮病肺病模式的不平衡数据分类。
机译:痴呆症预测中的数据挖掘方法:线性判别分析逻辑回归神经网络支持向量机分类树和随机森林的准确性敏感性和特异性的真实数据比较
机译:痴呆症预测中的数据挖掘方法:线性判别分析,逻辑回归,神经网络,支持向量机,分类树和随机森林的准确性,敏感性和特异性的真实数据比较