搜索资源列表
onTextCategorization
- 本文比较研究了在中文文本分类中特征选取方法对分类效果的影响。考察了文档频率DF、信息增 益IG、互信息MI、V2分布CHI 四种不同的特征选取方法。采用支持向量机(SVM) 和KNN两种不同的分类 器以考察不同抽取方法的有效性。实验结果表明, 在英文文本分类中表现良好的特征抽取方法( IG、MI 和 CHI)在不加修正的情况下并不适合中文文本分类。文中从理论上分析了产生差异的原因, 并分析了可能的 矫正方法包括采用超大规模训练语料和采用组合的特征抽取方法。最后通过实验验证组合特征
Semi-supervised-learning
- 义了一个欧氏距离和监督信息相混合的新的最近邻计算函数，从而将K一均值算法很好地应用于半 监督聚类问题。针对K一均值算法初始质心敏感的缺陷，用粒子群算法的搜索空间模拟聚类的欧氏空间，迭代搜 索找到较优的聚类质心，同时提出动态管理种群的策略以提高粒子群算法搜索效率。算法在UCI的多个数据集 上测试都得到了较好的聚类准确率。-Righteousness of a Euclidean distance and supervision of a mixture of new nearest n
Optimization2
- 组合优化求解旅行推销员问题， 近邻法、加权法-Combinatorial optimization to solve the traveling salesman problem, the nearest neighbor method, weighting method
parzen-kn
- 用matlab进行概率密度函数的非参数估计，主要有parzen窗法和kn近邻法。分别对平均分布和正态分布进行了仿真。-Non-parametric estimation of the probability density function using matlab, main the parzen window method and kn nearest neighbor method. The average distribution and normal distribution were
FaceRec
- PCA+三阶近邻法人脸识别 已进行实验，绝对有用-PCA+ third-order nearest neighbor algorithm, face recognition has been experimental, definitely useful
Umoshishibies
- 先用C-均值聚类算法程序，并用下列数据进行聚类分析。在确认编程正确后，采用蔡云龙书的附录B中表1的Iris数据进行聚类。然后使用近邻法的快速算法找出待分样本X（设X样本的4个分量x1=x2=x3=xx4=6；子集数l=3）的最近邻节点和3-近邻节点及X与它们之间的距离.-C-means clustering procedure, and the following data and cluster analysis. Confirm the programming is correct, Ca
knn
- knn实现，详细的最近邻算法的实现方法，简单易懂-knn achieve detailed nearest neighbor algorithm, easy to understand
downSample
- 实现图像下采样，实现的采样方法有最邻近采样法、二次插值法、双三次卷积法。-Image sampling, the sampling method to achieve the nearest neighbor sampling method, the quadratic interpolation, bicubic convolution.
knn_train
- 最小近邻法，融入了多重剪辑法，已通过验证。-Minimum nearest neighbor method, into a multi-clip method, has been verified.
K-negibour-method
- 利用K近邻法实现数字识别算法。误差小，识别效率高，网络训练速度快。-K-nearest neighbor algorithm, digital identification algorithm. Error is small, high recognition efficiency and speed of network training.
Pattern-Recognition_MATLAB_1
- 线性分类器设计，1_k近邻法，剪辑法，ANN-BP神经网络法，聚类分析法，特征选择，特征提取等模式识别常用算法，内有matlab可运行实现，还有word文档的说明。对于学习，是做好的资料。-Commonly used algorithm for linear classifier design the 1_k nearest neighbor, clip, ANN-BP neural network method, cluster analysis, feature selection, fea
NNearestneighe
- 模式识别问题最近邻算法的matlab实现，可以模拟实现现最近邻法的核心，是一个不错的代码，已通过测试。 -Pattern recognition problem neighbor algorithm matlab implementation can simulate the core of the nearest neighbor method is a good code has been tested.
20257147knn
- knn最近邻算法在给定新文本后，考虑在训练文本集中与该新文本距离最近（最相似）的 K 篇文本，根据这 K 篇文本所属的类别判定新文本所属的类别，具体的算法步骤如下： 一、:根据特征项集合重新描述训练文本向量 二、:在新文本到达后，根据特征词分词新文本，确定新文本的向量表示 三、:在训练文本集中选出与新文本最相似的 K 个文本-knn nearest neighbor algorithm in the given text, to consider in the train
knn
- In pattern recognition, the k-nearest neighbor algorithm (k-NN) is a method for classifying objects based on closest training examples in the feature space.
knn_myself
- KNN经典程序。用于经典非线性计算。-K-Nearest Neighbor code, by myself.
knn
- K近邻分类器，用于模式识别等领域，该程序短小精悍，适合与ANN和SVM进行比较研究，本人多篇论文用到，效果较好。-K-nearest neighbor classifier is often used in pattern recognition and other fields. It is suitful for a comparative study with ANN and SVM. I have published some papers used the code. The effe
KKNNn
- Knn算法综述、柔性KNN算法研究、一个高效的knn分类算法法、一种改进的KNN分类算法、一种优化的K最近邻协同过滤算法。 -The Knn algorithm summarized flexible KNN algorithm, an efficient knn classification algorithm method, an improved KNN classification algorithm, an optimized K nearest neighbor collabor
C-kNN
- c-knn最近邻算法源代码,最好的多示例算法之一,可运行-c-knn nearest neighbor algorithm source code, one of the best multi-sample algorithm can be run
Skongjianchazu
- 空间插值方法汇总Inverse Distance to a Power（反距离加权插值法） Kriging（克里金插值法）Minimum Curvature（最小曲率）Modified Shepardd s Method（改进谢别德法）Natural Neighbor（自然邻点插值法）Nearest Neighbor（最近邻点插值法）Polynomial Regression（多元回归法）Radia -Spatial interpolation method summary Inverse
near
- Image Demosaicing by nearest-neighbor interpolation method