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Algorithm-SVMLight

  • When working with mathematical simulations or engineering problems, it is not unusual to handle curv

    When working with mathematical simulations or engineering problems, it is not unusual to handle curves that contains thousands of points. Usually, displaying all the points is not useful, a number of them will be rendered on the same pixel since the screen precision is finite. Hence, you use a lot of resource for nothing! This article presents a fast 2D-line approximation algorithm based on the Douglas-Peucker algorithm (see [1]), well-known in the cartography community. It computes a hull, scaled by a tolerance factor, around the curve by choosing a minimum of key points. This algorithm has several advantages: 這是一個基于Douglas-Peucker算法的二維估值算法。

    標簽: mathematical engineering simulations problems

    上傳時間: 2013-12-20

    上傳用戶:changeboy

  • On-Line MCMC Bayesian Model Selection This demo demonstrates how to use the sequential Monte Carl

    On-Line MCMC Bayesian Model Selection This demo demonstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.

    標簽: demonstrates sequential Selection Bayesian

    上傳時間: 2016-04-07

    上傳用戶:lindor

  • The program implements three large-margin thresholded ensemble algorithms for ordinal regression. I

    The program implements three large-margin thresholded ensemble algorithms for ordinal regression. It includes an improved RankBoost algorithm, the ORBoost-LR algorithm, and the ORBoost-All algorithm.

    標簽: large-margin thresholded implements algorithms

    上傳時間: 2014-10-28

    上傳用戶:zhichenglu

  • The software implements particle filtering and Rao Blackwellised particle filtering for conditionall

    The software implements particle filtering and Rao Blackwellised particle filtering for conditionally Gaussian Models. The RB algorithm can be interpreted as an efficient stochastic mixture of Kalman filters. The software also includes efficient state-of-the-art resampling routines. These are generic and suitable for any application. For details, please refer to Rao-Blackwellised Particle Filtering for Fault Diagnosis and On Sequential Simulation-Based Methods for Bayesian Filtering After downloading the file, type "tar -xf demo_rbpf_gauss.tar" to uncompress it. This creates the directory webalgorithm containing the required m files. Go to this directory, load matlab and run the demo.

    標簽: filtering particle Blackwellised conditionall

    上傳時間: 2014-12-05

    上傳用戶:410805624

  • LEGClust算法更新

    LEGClust算法更新,上次上傳的代碼發現有些問題,現已更正,A Clustering Algorithm Based on Layered Entropic Subgraphs

    標簽: LEGClust 算法 更新

    上傳時間: 2013-12-20

    上傳用戶:yiwen213

  • KMEANS Trains a k means cluster model.CENTRES = KMEANS(CENTRES, DATA, OPTIONS) uses the batch K-mean

    KMEANS Trains a k means cluster model.CENTRES = KMEANS(CENTRES, DATA, OPTIONS) uses the batch K-means algorithm to set the centres of a cluster model. The matrix DATA represents the data which is being clustered, with each row corresponding to a vector. The sum of squares error function is used. The point at which a local minimum is achieved is returned as CENTRES.

    標簽: CENTRES KMEANS OPTIONS cluster

    上傳時間: 2014-01-07

    上傳用戶:zhouli

  • Probability distribution functions. estimation - (dir) Probability distribution estimation. dsam

    Probability distribution functions. estimation - (dir) Probability distribution estimation. dsamp - Generates samples from discrete distribution. erfc2 - Normal cumulative distribution function. gmmsamp - Generates sample from Gaussian mixture model. gsamp - Generates sample from Gaussian distribution. cmeans - C-means (or K-means) clustering algorithm. mahalan - Computes Mahalanobis distance. pdfgauss - Computes probability for Gaussian distribution. pdfgmm - Computes probability for Gaussian mixture model. sigmoid - Evaluates sigmoid function.

    標簽: distribution Probability estimation functions

    上傳時間: 2016-04-28

    上傳用戶:13188549192

  • 堆排序算法

    堆排序算法,the heap sort algorithm

    標簽: 排序算法

    上傳時間: 2016-05-04

    上傳用戶:磊子226

  • 支持向量機

    支持向量機,用于分類。Classify using (a very simple implementation of) the support vector machine algorithm

    標簽: 支持向量機

    上傳時間: 2014-01-11

    上傳用戶:hphh

  • Interface for Microsoft Audio Compression Manager. - Delphi Source The ACM uses existing driver i

    Interface for Microsoft Audio Compression Manager. - Delphi Source The ACM uses existing driver interface hooks to override the default mapping algorithm for waveform audio devices. This allows the ACM to intercept device-open calls. After a call has been intercepted, the ACM can perform a variety of tasks to process the audio data, such as inserting an external compressor or decompressor into the sequence.

    標簽: Compression Interface Microsoft existing

    上傳時間: 2013-12-13

    上傳用戶:541657925

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