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Semi-supervised Learning by Entropy Minimization
- Semi-supervised Learning by Entropy Minimization
基于贝叶斯网络的半监督聚类集成模型
- 已有的聚类集算法基本上都是非监督聚类集成算法,这样不能利用已知信息,使得聚类集成的准确性、鲁棒性和稳定性降低.把半监督学习和聚类集成结合起来,设计半监督聚类集成模型来克服这些缺点.主要工作包括:第一,设计了基于贝叶斯网络的半监督聚类集成(semi-supervised cluster ensemble,简称SCE)模型,并对模型用变分法进行了推理求解;第二,在此基础上,给出了EM(expectation maximization)框架下的具体算法;第三,从UCI(University of Ca
semi01.rar
- 近三年来半监督学习的国外顶级期刊论文，办监督的最新研究成果,Over the past three years semi-supervised learning of foreign top-level journal articles, to do oversight of the latest research results
nk2
- 半监督异常行为监测pdf，提出新的基于半监督学习的行为建模与异常检测方法，采用基于动态时间归整的归一化距离来建立相似矩阵-Semi-supervised monitoring abnormal behavior pdf, propose a new semi-supervised Learning based on behavior modeling and anomaly detection methods, based on Dynamic Time Warping of the norma
F-0358
- Semi-Supervised algorithm based on Fuzzy C-Means
Support-vector-machine-
- 利用谱聚类方法在特 征向量空间中对原始样本数据进行重新表述使得在新表述中同一聚类中的样本能够更好地积聚在一起构建聚类核函数 并进而构造聚类核半监督支持向量机 使样本更好地满足半监督学习必须遵循的聚类假设 -Restated in the new formulation in the same cluster sample be better able to accumulate together to build the clustering of nuclear function and
based-on-random-walk
- 随机游走在计算机学科的信息检索领域已经得到了成功的应用，现在正被 越来越多地应用到机器学习和数据挖掘等领域。在此背景下，我们提出图上的 随机游走学习，创造性地将随机游走作为一项基本技术，用于改善传统的有监 督学习，半监督学习和无监督学习中的困难问题-Random walk has been successfully applied in computer science, information retrieval, is now being increasingly applied
ssl-on-locally--multiple-graphs
- 一种用于multiple graphs的半监督学习-Efficient semi-supervised learning on locally informative multiple graphs
semi-supervized-learning
- A PhD thesis on Semi-supervised learning with Graphs by Xiaojin Zhu. Focuses on creating graphs, based on a mixture of labeled and unlabeled data (as per the semi-supervised learning paradigm) and using processes on these graphs to propagate in rigo
fenlei
- 空间约束半监督高斯过程下的高光谱图像分类 -Space constraints Semi-supervised hyperspectral image classification under the Gaussian process
Cost
- COST-SENSITIVE SEMI-SUPERVISED DISCRIMINANT ANALYSIS FOR FACE RECOGNITION Abstract: In our Project, we present a cost-sensitive semi-supervised discriminant analysis method for face recognition. In previous methods of dimensionality reductio
Using-Semi-supervised-Classifiers-for-Credit-Scor
- Using Semi-supervised Classifiers for Credit Scoring
paper4
- Provable Learning of Overcomplete Latent Variable Models Semi-supervised and Unsupervised Settings
0000007689
- 半监督流行学习算法，看后能懂得流行学习算法的基本原理-Popular semi-supervised learning algorithm, after watching can understand the basic principles of popular learning algorithm
AL-MULTICLASS
- Documentation for active learning and Semi supervised Learning two important machine learning algorithm