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05040031
- 文件包含有5项内容： 一、扩展卡尔曼滤波EKF 二、去偏转换卡尔曼滤波CMKF 三、最小二乘拟和的方法 四、最小二乘、EKF、CMKF的比较 五、野值剔除算法 用MATLAB实现了这些具体算法和要求 -document contains five elements : an extended Kalman Filter EKF two, Partial conversion to CMKF three Kalman filtering, and the least s
weightpercent
- Returns weighted percentiles of a sample given the weight vector w ％ The idea is to give more emphasis in some examples of data as compared to ％ others by giving more weight. For example, we could give lower weights to ％ the outliers. ％ The
matlab
- 可以剔除数据中的异常值，一个很实用的matlab小程序。-Can remove outliers in the data, a very useful little program matlab.
removeoutliers
- 采用matlab工作环境，利用Thompson Tau进行异常值剔除-Remove outliers from data using the Thompson Tau method.
Untitled4
- 剔除数据异常值，这个程序是比较小一点的 -Remove data outliers, this procedure is relatively smaller
JLinkage
- J-linkage 算法，可以用于多体拟合的一种策略，优于Multi-ransac-This paper tackles the problem of fitting multiple instances of a model to data corrupted by noise and outliers. The proposed solution is based on random sampling and conceptual data representation. Each poin
pr
- 关于模式识别的一些文章，离群点的检查，svm的介绍，最优化设计-A number of articles on pattern recognition, inspection of outliers, svm introduction, the most optimal design
LIBRA_19jun09
- Our toolbox currently contains implementations of robust methods for location and scale estimation, covariance estimation (FAST-MCD), regression (FAST- LTS, MCD-regression), principal component analysis (RAPCA, ROBPCA), princi- pal component re
weka-src
- weka源代码 最全最新的 数据挖掘用机器学习实现。包含聚类 分类 关联规则 离群点监测。java平台-weka most up-to-date source of data mining using machine learning to achieve. Clustering association rules classification contains outliers monitoring. java platform
xuzhuol
- 基于改进K-means的压缩IP 由于k-means本身受异常点影响较大，这里采用迭代k-means的方法，降低异常点的影响，减少计算量和提高聚类数目的灵活性。并添加合并异常聚类方法，提高聚类的均匀性-K-means based on improved compression IP As k-means itself is influenced by outliers, where an iterative k-means method to reduce the impact of o
Least_Squares_optimal_affine_subspace
- 最小二乘优化算法。Matlab源码，直接可以使用。-Least Squares optimal affine subspace The zip includes: (1) lsqAffineSpace: a low level routine that takes a set of m-dimensional real sample data and returns the optimal-fit k-dimensional affine subspace, with some
TimeSeriesPredictionUsingSupportVectorRegressionNe
- 为了选择神经网络的最好结构以及增强模型的推广能力，提出一种自适应支持向量回归神经网络(SVR—NN)。SVR—NN 用支持向量回归(SVR)方法获得网络的初始结构和权值， 白适应地生 成网络隐层结点，然后用基于退火过程的鲁棒学习算法更新网络结点疹教和权 主。 SVR—NN有很 好的收敛性和鲁棒性，能抑制由于数据异常和参数选择不当所导致的“过拟合，’现象。将SVR—NN 应用到时间序列预测上。结果表明，SVR．NN预测模型能精确地预测混沌时间序列，具有很好的 理论和应用价值。-Ab
KalmanFilter-POS
- 基于新息正交性的Kalman滤波抗野值法在POS中的应用-Based on new information orthogonality Kalman filter outliers in POS Application
rgpca.tar
- Robust GPCA This package consists of implementations of three robust techinques to robustify GPCA-Voting in the presence of large amounts of outliers. For function details, please read the README file in the package.
removeoutliers123
- Uses the Thompson Tau technique to remove outliers from a vector containing statistical data
SVM_Short-term-Load-Forecasting
- 优秀论文及配套源码。首先阐述了负荷预测的应用研究现状，概括了负荷预测的特点及其影响因素，归纳了短期负荷预测的常用方法，并分析了各种方法的优劣；接着介绍了作为支持向量机（SVM）理论基础的统计学习理论和SVM的原理，推导了SVM回归模型；本文采用最小二乘支持向量机（LSSVM）模型，根据浙江台州某地区的历史负荷数据和气象数据，分析影响预测的各种因素，总结了负荷变化的规律性，对历史负荷数据中的“异常数据”进行修正，对负荷预测中要考虑的相关因素进行了归一化处理。LSSVM中的两个参数对模型有很大影响，
removee
- removing outliers from a vector containing statistical data
outliers
- 原创的的matlab命令，能够处理化工过程中的异常点，是化工过程数据矫正的基础 -The original matlab command, it s able to solve outliers in the chemical process, it is the basis of chemical process data correction
outliers
- remove outliers based on Thompson Tau by M Sohrabinia
delete-outliers
- 用于去除一个数据集中的野点的matlab函数，可应用数据建模及统计分析-For input vector A, returns a vector B with outliers (at the significance level alpha) removed. Also, optional output argument idx returns the indices in A of outlier values. Optional output argument outlie