搜索结果: 1-15 共查到“相关回归分析”相关记录111条 . 查询时间(1.843 秒)
带特定标记的分位数回归模型
特定标记 分位数 回归模型
2023/12/13
Quantile regression has become a widely used tool for analysing competing risk data. However, quantile regression for competing risk data with a continuous mark is still scarce. The mark variable is a...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Best subset selection via distance covariance
距离协方差 最佳子集 回归分析
2023/4/14
Best subset selection is an important problem in regression analysis,which has many applications in computer science and medicine. However, the existing best subset selection methods have some limitat...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：A Sparse Expansion of (Deep) Gaussian Processes
深层 高斯过程 稀疏展开
2023/4/18
Conventional inferential methods for (deep) Gaussian Processes models can suffer from high computational complexity as they require large-scale operations with kernel matrices for training and inferen...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Probabilistic HIV Recency Classification -- A Logistic Regression without Labeled Individual Level Training Data
概率 HIV新近度分类 个人水平训练数据 逻辑回归
2023/4/24
Accurate HIV incidence estimation based on individual recent infection status (recent vs long-term infection) is important for monitoring the epidemic, targeting interventions to those at greatest ris...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Sequential implementation of reconstruction regression
重建回归 顺序实现 空间填充设计
2023/4/26
We propose a sequential method for implementing reconstruction regression. With a space-filling design of a small sample size, we use GP interpolation-based reconstruction regression to build initial ...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：A method to deal with generalized linear regressions in big data
处理 大数据 广义线性回归
2023/4/28
This paper proposes a method to accelerate calculation for generalized linear models in big data. We separate the covariates of full model into several groups to build candidate models. In the process...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Defocusing NLS equation with nonzero background: Painleve asymptotics in transition region
非零背景 散焦NLS方程 过渡区 疼痛渐近
2023/5/5
Consider to the Cauchy problem of the defocusing NLS equation with a nonzero background. With the Dbar steepest descent method and double scaling limit, we obtain Painleve asymptotics in two transitio...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Defocusing NLS equation with nonzero background: Soliton resolution in soliton region
非零背景 散焦NLS方程 孤子区域 孤子分辨率
2023/5/5
Consider to the Cauchy problem of the defocusing NLS equation with a nonzero background. With the Dbar generalization of the nonlinear steepest descent method to compute the leading order approximatio...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Percolation in Strongly Correlated Systems: The Massless Gaussian Field
强相关系统 渗透 无质量 高斯场
2023/5/5
In this talk, we will show several results for correlated nearest neighbor site percolation on Z^d. In particular, we will show that in three dimensions the strongly correlated massless harmonic cryst...
在许多现实的机器学习应用场景中,获取大量未标注的数据是很容易的,但标注过程需要花费大量的时间和经济成本.因此,在这种情况下,需要选择一些最有价值的样本进行标注,从而只利用较少的标注数据就能训练出较好的机器学习模型。
基于逻辑回归函数的加权K-means聚类算法
欧式距离 特征加权的K-means算法 逻辑回归函数 初始聚类中心
2022/3/15
传统K-means聚类算法通过欧式距离计算样本的相似度，将数据所有的属性特征均平等对待，忽略每个属性特征的不同贡献，导致样本相似度计算的准确率不高。针对这个不足，提出一种特征加权的K-means算法进行优化。首先，运用Softmax和Sigmoid逻辑回归函数计算特征权重，使得加权的欧式距离更能准确地表示样本相似度；其次，优化初始聚类中心选择策略，选择距离较大的K个样本作为初始聚类中心，可有效避免...
股票信息挖掘与LSTM预测
股票预测 长短时记忆神经网络（LSTM） 回归分析
2022/3/23
由于受到经济环境、政治政策、市场新闻等多种因素的影响，使得预测股票动态变得极具挑战性。研究了5种常用的预测股价变动的预测方法，通过逐步增加模型的输入维度进行预测分析。首先，建立5种优化的预测模型——基于时间序列的自回归平均模型(ARMA)、灰色预测模型(GM(1,1))、BP神经网络模型(BPNN)、基于改进网格寻优算法的支持向量回归(SVR)模型、基于Tensorflow的长短时记忆神经网络模型...
湖南工商大学2021年硕士研究生入学考试加试自命题应用回归分析考试大纲。
杭州电子科技大学经济学院2021年硕士研究生同等学力加试计量经济学考试大纲。