搜索资源列表
MVSOFGA
- 基本遗传算法，使用验证函数验证！结果非常准确！-basic genetic algorithm, the use of certification function validation! Very accurate results!
crossvalidate
- 基于决策树的n则交叉验证分类器 （决策树程序直接调用matlab中的） crossvalidate.m N则交叉验证程序，N可选 NDT.mat 含9个国际公认标准数据集，已做过标么处理，可直接使用 专业-n Based on Decision Tree is cross-validation classification (decision tree directly call the Matlab) cr ossvalidate.m N is cross-validation
基于NSVM的SVM分类器
- 基于NSVM的两类SVM分类器，matlab7.1运行通过，main中做了PCA的特征提取、leave one out cross-valiation和5-fold cross-validation（重复10次的平均值）
trnn
- 神经网络训练，应用matlab7NN包，用一个隐藏层使用5折交叉验证。-Training the Neural Network This scr ipt is something that I did for a course at Uni. It uses the Neural Networking package provided with MatLab 7 unfortunately I m not sure if it s available with the earlier ve
FeatureSelection
- Feature Selection using Matlab. The DEMO includes 5 feature selection algorithms: • Sequential Forward Selection (SFS) • Sequential Floating Forward Selection (SFFS) • Sequential Backward Selection (SBS) • Se
CrossValidationTest20081008203828
- classification cross validation
alinfo
- file for cross validation
shenjingwangluo
- 里面有两个实验，包括PPT和实验的代码，可以帮助一些想学习神经网络的朋友一个大忙。-We now have an easy scr ipt (easy.py) for users who know NOTHING about svm. It makes everything automatic--from data scaling to parameter selection. The parameter selection tool grid.py generates the follo
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
GAbp
- 用遗传算法优化bp神经网络的权值，并训练以及验证网络-Bp by using genetic algorithms to optimize the weights of neural networks, and network training and validation
111
- LIBSVM是台湾大学林智仁(Lin Chih-Jen)副教授等开发设计的一个简单、易于使用和快速有效的SVM模式识别与回归的软件包，他不但提供了编译好的可在Windows系列系统的执行文件，还提供了源代码，方便改进、修改以及在其它操作系统上应用；该软件还有一个特点，就是对SVM所涉及的参数调节相对比较少，提供了很多的默认参数，利用这些默认参数就可以解决很多问题；并且提供了交互检验(Cross Validation)的功能。
J48cv
- 基于决策树的n则交叉验证分类器-based on decision tree cross-validation classifier.....................
Inertiadevicefaultpredictionbasedonwavelet
- ：为了提高最小二乘支持向量回归机的性能，将Morlet小波核函数引入其中，形成了最小二乘小波支 持向量回归机模型。利用待优化的参数重构模型的目标函数和约束条件，并在此基础上通过遗传算法进行参数 选择，从而提高了该模型的泛化能力。将最小二乘小波支持向量回归机应用于导弹陀螺仪的漂移趋势预测，仿真 实验结果表明了该方法的有效性和可行性，因此可以为陀螺仪的故障预报、可靠性辅助决策提供依据。-To improve the ability of least square support vect
AI_Blood
- 本次大作业利用K‐近邻（K‐Nearest Neighbor）算法，为给定的训练数据集构造了分类器， 并在测试数据集上进行分类预测，同时计算了Accuracy、Precision、Recall和F‐measure，利用 10‐fold的实验方法进行交叉验证。-The big job to use K-neighbor (K-Nearest Neighbor) algorithm, for a given set of training data classifier is constru
CellSort_1.1
- This toolbox includes routines for using principal component analysis (PCA) and independent component analysis (ICA) to extract cellular signals from imaging data sets. A full descr iption and validation of the method is provided in the paper, "Autom
geneticalgorithm
- 通信建模领域的遗传算法。本算法提供14个参数可供修改验证。每个参数都有具体英文解释，对于通信建模的初步认识有很大的帮助。-Modeling the field of communications genetic algorithm. This algorithm can be modified to provide 14 parameter validation. Each parameter has a specific interpretation in English, for an in
Ex1
- 模式识别某次课程的作业，完成了高斯分布下的两种贝叶斯分类器,以及非参数的K近邻、Parzen窗方法，采用UCI机器学习数据库中的某些数据作为样本，使用交叉验证方法确定参数-Pattern recognition of a particular course work, completed under the two Gaussian Bayesian classifier, and the non-parametric K-nearest neighbor, Parzen window meth
bpcross
- 一个matlab写的bp人工神经网络程序，参数优化采用交叉验证办法-Write a matlab bp artificial neural network program, parameter optimization using cross-validation method
l2trStMKL.tar
- Cross-Validation (matlab code)
kfold_cv-master
- divide your data set into training and validation sets for n-fold cross-validation.