本文针对计算光学切片中的最近邻算法提出了一种改进算法。
An improved nearest neighbor subtraction algorithm was presented and applied in the Computational Optical Section Microscopy (COSM).
最近邻算法可被扩展成不仅仅限于一个最近匹配，而是可以包括任意数量的最近匹配。
The Nearest Neighbor algorithm can be expanded beyond the closest match to include any number of closest matches.
传统的K-近邻算法选择的相似性度量通常是欧几里德距离的倒数，这种距离通常涉及所有的特征。
The Euclidean distance is usually chosen as the similarity measure in the conventional K-NN algorithm, which usually relates to all attributes.
其次本文实现了异常点挖掘最常用的两类基于距离的算法：DKP最近邻算法和基于LOF密度的算法。
Meanwhile, 2 kinds of distance-based algorithms are implemented: DKP neighbor algorithm and LOF density algorithm both are vital for the rest of the paper.
如果使用最近邻算法回答我们上面遇到的“第5个顾客最有可能购买什么产品”这一问题，答案将是一本书。
To answer the question "What is Customer No. 5 most likely to buy?" based on the Nearest Neighbor algorithm we ran through above, the answer would be a book.
特征权重学习是基于特征赋权的K近邻算法需要解决的重要问题之一，传统上提出了许多启发式的学习方法。
Feature weighting is one of the important problems for feature weighting based KNN algorithm, and many heuristic methods have been employed to solve the problem traditionally.
最近邻算法是用来作为预测模型预测蛋白质的亚细胞位置，并获得一个正确的预测准确率70.63％，刀切交叉验证评估。
Nearest Neighbor Algorithm is used as a prediction model to predict the protein subcellular locations, and gains a correct prediction rate of 70.63%, evaluated by Jackknife cross-validation.
依据同源连续性原理，通过分析高维空间中向量的方向和点的位置关系来研究模糊图像与原图像的空间关系，并且结合最近邻算法，将该算法应用于去除最近邻算法所得图像的本层模糊。
To recover blurred image but the PSF of the image was not known, using the method which according to homeomorphisms and the principle of homology continuity(PHC) in high-dimensional space geometry.
最近邻技术最后的一个挑战是该算法的计算成本有可能会很高。
The final challenge with the Nearest Neighbor technique is that it has the potential to be a computing-expensive algorithm.
反向最近邻查询是空间数据库中最重要的算法之一。
One of the most important algorithms in spatial database is reverse nearest neighbor query.
该模型包括历史样本数据库、近邻子集搜索程序、近邻子集优化算法和预报量估计技术。
This model includes a historical database, a procedure of searching for the nearest neighbor subset and its optimization algorithm and the technique of predict and estimation.
提出并实现了一种结合前馈型神经网络和K最近邻的文本分类算法。
This paper put forward and carried out a text classification method using feed-forward neural network and K-nearest neighbor.
改进后的算法缩小了最近邻点的搜索范围，提高了运算效率。
In the improved algorithm, the search field for the nearest neighbor is reduced, resulting in increased efficiency.
该方法利用模式识别中的近邻准则，使用元胞蚂蚁算法实现故障的分类，达到故障诊断的目的。
The method realizes classification of fault by near-neighborhood criteria of pattern recognition and cellular ant algorithm.
改进跟踪起始和跟踪终结算法，用卡尔曼滤波预测位置，最近邻原则进行数据关联，实现了对实验图像中多个目标的良好跟踪。
It succeeds in exemplificative images by improving the method of tracking origination and finality, using Kalman Filter to forecast the next position and the nearest rule to associate data.
本文研究三种在近邻分类法基础上的改进算法：（1）编辑技术，（2）边界抽取，（3）边界补缀。
This paper analysis three different kinds of improved algorithms based onthe K-NN classification:(1) Editing technique, (2) Boundary extraction, (3) Boundarypatching.
其次滤除受高斯噪声污染的像素点，采用对称近邻均值滤波算法。
Following that the Gaussian noises are filtered out by symmetrical-neighbor mean filtering.
该模型首先采用改进的最近邻聚类算法确定径向基函数中心，接着应用递推最小二乘法训练网络的权值。
The model USES an improved nearest-neighbor clustering algorithm to select the RBF center, and a recursive least square algorithm to train weights of the RBF neural network.
其中消极学习型中应用最广泛的是最近邻分类算法。
In those lazy learning algorithms most extensively used is nearest neighbor classification (NN) algorithm.
针对这个缺点，提出了一种改进的、基于自适应最近邻法的局部线性嵌入方法，数值实验证明算法对于有监督的学习问题，具有较好的适应性。
An adaptive nearest neighbor locally linear embedding algorithm is proposed to overcome this shortage. Experiment results show that the algorithm ADAPTS well the supervised learning problems.
将该方法与K—最近邻判决规则结合，提出了用于判别的固定邻域判决算法。
Combining this method with the K-nearest neighbor decision rule, a fixed neighborhood, decision algorithm is developed.
辨识器采用RBF神经网络结构和最近邻聚类算法，实现了对系统逆动力学模型的动态辨识。
The system identifier based on RBF neural network which applies nearest neighbor clustering algorithm realizes the identification of the inverse dynamic system model.
阐述了基于相似度理论的最近邻居算法检索策略，能够对实例库中的实例进行检索。
The nearest neighbor algorithm a type of retrieval strategy based on similarity theory is described, and the case in the case base can be retrieved.
对改进的标准问题进行测试，同时与最近邻域搜索算法的结果作比较，结果表明算法是有效的。
Compared to nearest neighborhood search algorithm, the algorithm was verified to be efficient through a number of standard test cases.
为了提高化学主题搜索引擎的查询效果，采用距离加权七一近邻分类算法来进行自动分类。
In order to improve the performance of chemistry-focused search engines, an automatic text categorization algorithm is proposed based on the distance-weighted k-nearest neighbor algorithm.
这主要是因为算法使用了K-近邻方法来求解最近邻点。
The reason is that the algorithm searches the nearest neighbor points with K-nearest neighbor.
实验结果表明，该算法的运算时间是改进的等均值等方差最近邻域搜索(IEENNS)算法的80%左右。
The experimental results show that the computing time for the new algorithm is 80% that of the improved equal-average equal-variance nearest-neighbor search (IEENNS) algorithm.
K最近邻的信号分离算法中，较多地采用了乐音信号的先验信息，一定程度上可实现信号分离。
The KNN based music source separation algorithm utilizes prior information of music source which can also achieve music source separation.
基于内容的过滤算法大多数是基于向量空间模型的算法，其中广泛使用的是朴素贝叶斯算法和K最近邻（KNN）算法。
Most of the content-based filtering algorithms are based on vector space model, of which Naive Bayes algorithm and K-Nearest Neighbor (KNN) algorithm are widely used.
基于内容的过滤算法大多数是基于向量空间模型的算法，其中广泛使用的是朴素贝叶斯算法和K最近邻（KNN）算法。
Most of the content-based filtering algorithms are based on vector space model, of which Naive Bayes algorithm and K-Nearest Neighbor (KNN) algorithm are widely used.
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