SSE:平方误差和
“平方误差和”(Sum of Squared Error,简称SSE)是一种常见的统计学概念,用于衡量数据点与其均值之间的偏差平方之和。该指标广泛应用于数据分析、机器学习及工程建模等领域,能够有效评估模型的拟合精度。通过缩写为SSE,便于在学术文献和技术交流中快速引用与书写。
Sum of Squared Error具体释义
Sum of Squared Error的英文发音
例句
- Furthermore, in order to solve the model selection problems of unsupervised image segmentation, the sum of squared error criterion with penalty term is proposed.
- 而且,针对无监督图像分割的模型选择问题提出了带惩罚项的误差平方和阶次判定准则。
- Simulation results demonstrate that the algorithm is better than the original one in the performance index of maximum error and sum of squared error.
- 仿真研究表明改进算法在最大偏差与误差平方和等方面的性能指标优于原算法。
- Data examples of membership function building are listed and we obtained the smallest sum of squared error of the membership function and the empirical data. In this way, the feasibility and superiority of the way for constructing fuzzy membership function using Bezier curve theory is verified.
- 根据构建隶属度函数的数据实例,求得隶属度函数与实证数据之间的最小的平方误差总和,验证了贝塞尔曲线方法对于构建模糊隶属度函数的可行性和优越性。
- The optimization function is defined to be the sum of the squared error between the previous trace and the current pattern representation.
- 我们定义优化目标函数为前时刻轨迹和当前时刻特征提取结果的均方误差和,推导了相应的轨迹学习算法。
- A new criterion for k-value selection, the key problem existed in ridge regression, was proposed based on the combination of the average predictive relative error with average self-checking relative error instead of the sum of predictive residual squared error.
- 提出改进的预报相对误差法选择岭回归参数k,以平均预报相对误差替代预报残差平方和,并抑制过拟合。
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