半监督学习

一种基于半监督学习的多模态Web查询精化方法

Multi-Modal Web Search Query Refinement Based on Semi-Supervised Learning

融入半监督学习的思想，提出了PCSEM算法。

Absorbing the main thoughts of semi-supervised learning , PC_SEM is presented .

针对用于BP网络训练的半监督学习算法，提出了一种新的实用的训练结束判据，并将其应用于电力系统暂态稳定分类中。

A useful ending-criterion is proposed for semi-supervised BP algorithm , and applied it to transient stability classification of power systems .

该方案使用的算法就是基于FCM的半监督学习算法，同时可以进行特征选择。

It uses semi-supervised learning algorithm based on FCM , and for feature selection .

实验结果表明，在小样本情况下，半监督学习方法比传统的HMM方法具有更高的识别率。

Experiment results prove that semi-supervised learning is more efficient than traditional HMM in syllable recognition .

使用一个半监督学习算法，ANN可产生一个能够指示相对稳定度的连续分布的暂态稳定指标。

The ANN can derive a continuous-spread stability index to indicate the relative stability degree by means of a semi-supervised learning algorithm .

半监督学习（semi-supervisedlearning）是利用未标记样本进行学习的主流技术，是目前机器学习中非常活跃的研究方向之一。

Semi-supervised learning is the primary method of making use of unlabeled samples for learning , and is a very active research field in machine learning .

实验结果表明，不对称的半监督学习策略及随机子空间理论可有效地改进SVM反馈性能，且所提出算法明显优于同类SVM反馈方法。

The experimental evaluations show that the proposed asymmetric semi-supervised learning methodology in conjunction with random subspace theory is effective to improve CBIR performance and achieves better performance than some existing approaches .

本论文提出了一种有效地结合SVM和LPP的半监督学习算法&LPP半监督算法。

In this thesis , we introduce a new semi-supervised learning algorithm : Semi-supervised LPP algorithm , which efficiently combines the characters of both SVM and LPP .

为了对在线学习文档进行分类，本文根据自适应谐振理论给出了一个半监督学习模糊ART模型（SLFART）及其算法。

For learning document classification on line , the paper gives the semi-supervised learning fuzzy ART model ( SLFART ) based on adaptive resonance theory and the models algorithm .

对三种半监督学习算法Self-Training、Co-Training和Tri-Training结合不同的基分类器通过实验来进行性能评估。

Based on different base classifier algorithms , experiments evaluate performance on three semi-supervised learning algorithms including Self-Training , Co-Training and Tri-Training .

该算法基于贝叶斯决策理论，通过概率密度函数进行分布估计，对两类别半监督学习问题进行判定。（3）给出了一个基于FCM的半监督学习算法。

The algorithm is based on Bayesian decision machinery , with estimation of the structure from probability density function , for two-class problems . ( 3 ) The paper gives out a semi-supervised learning algorithm based on FCM .

本文在深入研究半监督学习和传统的机器学习理论及目前入侵检测系统所面临问题的基础上，选择SVM方法作为基础分类算法，提出了一种新的处理海量未标记数据的半监督算法。

SVM has been recently used in many applications . We deeply research the Semi-supervised Learning , machine learning and the problems of current intrusion detection system . The research in this paper provides new methods based on SVM for solving mass unlabeled data .

同时，RCAS算法结合了机器学习中半监督学习和相关反馈算法的优点，对有关类和无关类中未标记样本采用不同的方式加以利用。

Meanwhile , RCAS employs semi-supervised learning and relevance feedback to deal with the unlabeled samples in the related class and unrelated class .

实验结果表明半监督学习自适应谐振理论系统的性能优于判别式CEM算法，特别是在含有噪音和新模式数据情况下，其优势更为明显。

Experimental results illustrate that the performances of the proposed system is better than the discriminant CEM ( classification expectation maximization ) algorithm , particularly when there are noise data and new patterns .

本文主要研究的是基于图的半监督学习方法与应用。

In this thesis , I focused on graph-based semi-supervised learning .

通常这样的学习问题也被称为半监督学习。

Usually , such problems are also known as semi-supervised learning .

基于半监督学习的行为建模与异常检测

Behavior Modeling and Abnormality Detection Based on Semi-Supervised Learning Method

基于半监督学习和支持向量机的眉毛识别方法研究

Study of Semi-Supervised Learning-Based and Support Vector Machine-Based Eyebrow Recognition

一种基于李群的半监督学习算法及应用研究

A Semi-Supervised Learning Algorithm Based on Lie Group and Application

提出了一种基于分类器集成的半监督学习算法。

Propose a semi-supervised learning algorithm based on ensemble learning .

半监督学习及其在指纹图像分割上的应用研究。

Semi-supervised learning and its applications to fingerprint image segmentation .

尝试研究了半监督学习在基于数据驱动的故障诊断方法中的应用。

Semi-supervised learning to data-driven fault diagnosis has been introduced .

基于半监督学习的蛋白质关系抽取研究

Research of protein-protein interaction extraction based on semi-supervised learning

半监督学习研究的目的是在整个数据集中只有一部分样本有标记的情况下，如何对数据进行分类。

The goal of semi-supervised learning is to learn from partially labeled data .

基于半监督学习的入侵检测算法研究

Study of Intrusion Detection Algorithm Based on Semi-supervised Learning

基于半监督学习和决策融合的人脸表情识别方法研究

Research on Expression Recognition Methods Based on Semi-Supervised Learning and Decision Level Fusion

半监督学习在入侵检测系统中的应用

Semi-supervised Learning and Its Application to Intrusion Detection System

基于图的半监督学习模型研究与分类器设计

Research on Graph-based Semi-Supervised Learning Model and Classifier Design

基于半监督学习的特定领域术语抽取算法的研究

Research on Domain-Specific Term Extraction Based on Semi-Supervised Learning