We often estimate the return model parameter by ordinary least squares and maximum likelihood. 对回归模型进行参数估计时,常用的两种重要方法是普通最小二乘法和最大似然(ML)法。
The result showed that the maximum likelihood algorithm possesses higher stability and suitability on the random measured noise. 结果表明极大似然算法对随机测量噪声具有更高的稳定性和适应性。
The second goal is the estimation method of maximum likelihood. 第二个目标是最大似然(ML)的估计方法。
A model and an algorithm were provided for constructing phylogenetic tree based on the principle of maximum likelihood estimate. 利用最大似然(ML)估计原理,给出了构建系统发生树的模型和算法。
Decision theory, statistical classification, maximum likelihood and Bayesian estimation, non-parametric methods, unsupervised learning and clustering. 决策理论,统计分类,最大似然(ML)和贝叶斯估计,非参数方法,非监督的学习与聚类。