K-Nearest相关论文
The nearest neighbors (NNs) classifiers, especially the k-Nearest Neighbors (kNNs) algorithm, are among the simplest and......
数据分析可以解决数据量大,数据结构复杂等问题,在医疗方面可对大量的医疗数据进行精准分析,本文主要研究监督学习算法中的决策树......
随着越来越多的数据累积,对数据处理能力和分析能力的要求也越来越高.传统k-Nearest Neighbor(k NN)查询算法由于其容易导致计算负......
图像的目标识别是模式识别的研究领域之一,现已广泛应用于视频监控、交通运输和动作识别等。受图像采集过程中光照变化、形状和噪......
Estimation of premature forests in Georgia (USA) using U.S.Forest Service FIA data and Landsat image
We used geographic information system applications and statistical analyses to classify young, premature forest areas in......
提出了一种基于密度的K邻近空间球搜索算法。这种算法先根据空间数据的范围和数据点的总数对点云进行空间划分,再以当前被测点作为......
本文提出了一种基于ICA的眉毛识别方法。在经过预处理的眉毛图像上,先用ICA算法对眉毛图像进行特征提取,得到其特征向量,然后用K-......
针对传统的模糊支持向量机（FSVM）算法对边缘噪声敏感的不足，提出一种基于非线性紧密度和K最近邻方法（KNN）相结合的FSVM算法。该方法在计......
Computational Intelligence Prediction Model Integrating Empirical Mode Decomposition,Principal Compo
On the basis of machine leaning,suitable algorithms can make advanced time series analysis.This paper proposes a complex......
传统的近邻模型（k-nearestNeighborhood，KNN）是一种使用广泛的协同过滤模型，但是随着用户和项目的增加，需要计算大量用户或项之间的相似......
随着Internet上维吾尔文信息的迅速发展,维吾尔文文本分类成为处理和组织这些大量文本数据的关键技术。研究维吾尔文文本分类相关......
将多载荷作用下的连续体结构拓扑优化设计看作为一种对单元样本的模式识别,然后利用模式识别的K邻近（KNN）方法实现连续体结构的拓扑......
不良短信的泛滥,严重影响了社会风气,干扰了人们正常的生活秩序,研发不良短信过滤技术具有相当的实用价值。应用中科院计算所研制......
针对图像聚类问题,提出了一种基于图像空间关系的聚类方法,采用场模型描述图像之间的空间关系,利用K-近邻思想构建图像邻域系统,聚......
In this paper,the application of an algorithm for precipitation retrieval based on Himawari-8 (H8) satellite infrared da......
In this paper, a memetic algorithm with competition(MAC) is proposed to solve the capacitated green vehicle routing prob......
Existing interference protection systems lack automatic evaluation methods to provide scientific, objective and accurate......
We developed a software performing laminae counting, thickness measurements, spectral and wavelet analysis of laminated ......
Arrhythmia beat classification is an active area of research in ECG based clinical decision support systems. In this pap......
Support Vector Machine-Based Fault Diagnosis of Power Transformer Using k Nearest-Neighbor Imputed D
Missing values are prevalent in real-world datasets and they may reduce predictive performance of a learning algorithm. ......
The EMG signal which is generated by the muscles activity diffuses to the skin surface of human body. This paper present......
The EM algorithm is a very popular maximum likelihood estimation method, the iterative algorithm for solving the maximum......
The detection and recognition of radar signals play a critical role in the maintenance of future electronic warfare(EW).......
This paper proposes a novel Multiple-Input Multiple-Output (MIMO) transmission scheme based on Pattern Recognition (PR),......
As climate change negotiations progress,monitoring biomass and carbon stocks is becoming an important part of the curren......
A Comparison of Selected Parametric and Non-Parametric Imputation Methods for Estimating Forest Biom
Various methods have been used to estimate the amount of above ground forest biomass across landscapes and to create bio......
To accurately identify soybean pests and diseases, in this paper, a kind of deep convolution network model was used to d......
