参数学习采用在线学习算法(online learning algorithm)，测试阶段(一阶生成树模型)则采用 Chu-Liu-Edmonds 最大生成 树算法，该算法具有 O(n 2 )的复杂度。
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This paper presents a color images region growing method based on online learning algorithm, which is used for content-based image retrieval systems.
论文阐述了一种基于在线学习算法的彩色图像区域增长法，用于解决基于内容的图像检索系统。
By using CMAC neural network based on credit assignment this algorithm is implemented, and conventional CMAC's online learning speed and its accuracy are improved at the same time.
采用基于信任分配的CMAC神经网络实现了该算法，显著提高了传统CMAC在线学习的速度与准确性。
To reduce the computational cost of extreme learning machine (ELM) online training, a new algorithm called local extreme learning machine (LELM) was proposed.
针对训练样本贯序输入时的极端学习机（ELM）训练问题，提出一种可实现在线训练的局域极端学习机（LELM）。
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