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libsvm-2.81
- Libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression. It can solve C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM regression. It also provides an automatic
ReversibleJumpMCMCSimulatedAnneaing
- This demo nstrates the use of the reversible jump MCMC simulated annealing for neural networks. This algorithm enables us to maximise the joint posterior distribution of the network parameters and the number of basis function. It performs a global se
particle-filter-mcmc
- 该程序为基于粒子滤波的一种新算法,综合MCMC Bayesian Model Selection即MONTE CARLO马尔克夫链的算法,用来实现目标跟踪,多目标跟踪,及视频目标跟踪及定位等,解决非线性问题的能力比卡尔曼滤波,EKF,UKF好多了,是我珍藏的好东西,现拿出来与大家共享,舍不得孩子套不着狼,希望大家相互支持,共同促进.-the program based on particle filter for a new algorithm, Integrated Bayesian MCMC
rjMCMCsa
- 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
svm
- libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression. It solves C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM regression. It also provides an automatic mo
svm_v0.55beta
- 最新的支持向量机工具箱，有了它会很方便 1. Find time to write a proper list of things to do! 2. Documentation. 3. Support Vector Regression. 4. Automated model selection. REFERENCES ========== [1] V.N. Vapnik, \"The Nature of Statistical Learning Theory\", Springer-Verl
autolife
- Autolife模型是一个能够进行“开放式进化”的人工生命系统。每个Agent模型采用可以变化规则表长度的有限自动机模型建模。一方面Agent可以进行自我繁殖，同时模型中的选择机制没有采用显式的适应度函数而是采用能量消耗的简单模型而自发涌现出来，所以可以认为Agent模型是一个类Tierra系统。然而与Tierra、Avida等数字生命模型不同的是，Autolife模型进行了大大的简化，它界面友好，操作直接。虽然没有给每个Agent装配一个虚拟计算机，但是Agent与环境的耦合则可以看成一个图灵
libsvm-2.85
- Libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression. It solves C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM regression. It also provides an automatic mo
libsvm-2.88
- 支撑向量机SVM的工具LIBSVM，能够在windows平台下通过命令行使用，也可以在matlab下调用，适合于研究复杂条件下的分类问题-Libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression. It solves C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM
1
- 关于人工免疫系统，克隆选择，免疫记忆的最新文献。并行人工免疫系统的塔式主从模型(Towerlike Master-Slave Model,TMSM),和基于TMSM的并行免疫记忆克隆选择算法-On artificial immune systems, clonal selection, immune memory, the latest literature. Parallel artificial immune system tower master-slave model (Towerlik
ruih
- 分析了人工免疫系统的原理,简单建立了一种基于否定选择算法的网络入侵检测系统, 引入了一种用于异常事件识别的r-字符块匹配规则,并对规则存在的漏洞进行了分析。 -The paper gives a brief introduction to the principle of Immune System·In particular,the paper gives a simple NIDS model based on negative selection algorithm,intro
mianyisuanfa
- 为求解大规模TSP 问题,提出了并行人工免疫系统的塔式主从模型( Towerlike Master2Slave Model , TMSM) ,和基于TMSM的并行免疫记忆克隆选择算法(Parallel Immune Memory Clonal Selection Algorithm ,PIMCSA) .- This paper presents a parallel model termed as towerlike master2slave model ( TMSM) for artifi
libsvm.tar
- library for SVMclassification and regression. It solves C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM regression. It also provides an automatic model selection tool for C-SVM classification.
libsvm-2.89
- 是一種線性方成的分類器。SVM透過統計的方式將雜亂的資料以NN的方式分成兩類，以便處理。LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized logistic regression (LR), L2-loss linear SVM, and L1-loss linear SVM. -Main features of LIBLINEA
MatlabSpiderToolbox
- Matlab人工智能学习包，由世界领先的德国马普所制作-The spider is intended to be a complete object orientated environment for machine learning in Matlab. Aside from easy use of base learning algorithms, algorithms can be plugged together and can be compared with, e.g model
SVMhybridsystem
- A distributed PSOSVM hybrid system with feature selection and parameter optimization -Abstract This study proposed a novel PSO–SVM model that hybridized the particle swarm optimization (PSO) and support vector machines (SVM) to improve the clas
Adaptive-Online-Learning
- 基于EKF的神经网络自适应在线学习算法，包含例子和文档。-We show that a hierarchical Bayesian modeling approach allows us to perform regularization in sequential learning. We identify three inference levels within this hierarchy: model selection, parameter estimation, and
spider
- 机器学习matlab源代码，包括多分类SVM，模式识别，特征选择，回归等算法。-The spider is intended to be a complete object orientated environment for machine learning in Matlab. Aside from easy use of base learning algorithms, algorithms can be plugged together and can be compared with
estimate_object_number_e.tar
- 该程序基于2D特征点的移动轨迹,估计独立运动的对象数目.-Given 2D trajectories of feature points moving in the image frame, this program estimates the number of independent motions using model selection by the geometric AIC (default) or the geometric MDL (option) based
ELSA_v0.1.tgz
- This package contains the code for the Enhanced Local Subspace Affinity (ELSA) with Enhanced Model Selection (EMS+) and number of motions estimation based on the eigenvalue spectrum of the Symmetric Normalized Laplacian matrix.-This package co