登录
首页 » WINDOWS » AdaBoost算法

AdaBoost算法

于 2017-12-23 发布 文件大小:7745KB
0 264
下载积分: 1 下载次数: 17
我要下载

代码说明：

  用matlab软件，实现adaboost算法。将数据集划分为训练集和测试集，给训练集的数据贴标签，用训练好的模型来测试测试数据的准确度。(Using Matlab to implement the AdaBoost algorithm. The data set is divided into training set and test set to label the data of the training set, and the accuracy of the test data is tested by the trained model.)

文件列表：

adaBoost-master
adaBoost-master\README, 604, 2017-01-03
adaBoost-master\bestLinearClassifier.in, 6705, 2017-01-03
adaBoost-master\classifyExample.m, 1157, 2017-01-03
adaBoost-master\computeIntegralImage.m, 1076, 2017-01-03
adaBoost-master\dataset
adaBoost-master\dataset\TestImages
adaBoost-master\dataset\TestImages\test-0.pgm, 24165, 2017-01-03
adaBoost-master\dataset\TestImages\test-1.pgm, 37690, 2017-01-03
adaBoost-master\dataset\TestImages\test-10.pgm, 30015, 2017-01-03
adaBoost-master\dataset\TestImages\test-100.pgm, 20840, 2017-01-03
adaBoost-master\dataset\TestImages\test-101.pgm, 10850, 2017-01-03
adaBoost-master\dataset\TestImages\test-102.pgm, 10850, 2017-01-03
adaBoost-master\dataset\TestImages\test-103.pgm, 34815, 2017-01-03
adaBoost-master\dataset\TestImages\test-104.pgm, 42043, 2017-01-03
adaBoost-master\dataset\TestImages\test-105.pgm, 37255, 2017-01-03
adaBoost-master\dataset\TestImages\test-106.pgm, 21071, 2017-01-03
adaBoost-master\dataset\TestImages\test-107.pgm, 16655, 2017-01-03
adaBoost-master\dataset\TestImages\test-108.pgm, 39075, 2017-01-03
adaBoost-master\dataset\TestImages\test-109.pgm, 23325, 2017-01-03
adaBoost-master\dataset\TestImages\test-11.pgm, 30015, 2017-01-03
adaBoost-master\dataset\TestImages\test-110.pgm, 39117, 2017-01-03
adaBoost-master\dataset\TestImages\test-111.pgm, 16185, 2017-01-03
adaBoost-master\dataset\TestImages\test-112.pgm, 18936, 2017-01-03
adaBoost-master\dataset\TestImages\test-113.pgm, 30612, 2017-01-03
adaBoost-master\dataset\TestImages\test-114.pgm, 10088, 2017-01-03
adaBoost-master\dataset\TestImages\test-115.pgm, 29902, 2017-01-03
adaBoost-master\dataset\TestImages\test-116.pgm, 20840, 2017-01-03
adaBoost-master\dataset\TestImages\test-117.pgm, 41375, 2017-01-03
adaBoost-master\dataset\TestImages\test-118.pgm, 19335, 2017-01-03
adaBoost-master\dataset\TestImages\test-119.pgm, 9854, 2017-01-03
adaBoost-master\dataset\TestImages\test-12.pgm, 14714, 2017-01-03
adaBoost-master\dataset\TestImages\test-120.pgm, 13314, 2017-01-03
adaBoost-master\dataset\TestImages\test-121.pgm, 21591, 2017-01-03
adaBoost-master\dataset\TestImages\test-122.pgm, 25923, 2017-01-03
adaBoost-master\dataset\TestImages\test-123.pgm, 12302, 2017-01-03
adaBoost-master\dataset\TestImages\test-124.pgm, 18108, 2017-01-03
adaBoost-master\dataset\TestImages\test-125.pgm, 20805, 2017-01-03
adaBoost-master\dataset\TestImages\test-126.pgm, 10639, 2017-01-03
adaBoost-master\dataset\TestImages\test-127.pgm, 17664, 2017-01-03
adaBoost-master\dataset\TestImages\test-128.pgm, 19450, 2017-01-03
adaBoost-master\dataset\TestImages\test-129.pgm, 40731, 2017-01-03
adaBoost-master\dataset\TestImages\test-13.pgm, 50715, 2017-01-03
adaBoost-master\dataset\TestImages\test-130.pgm, 38295, 2017-01-03
adaBoost-master\dataset\TestImages\test-131.pgm, 28923, 2017-01-03
adaBoost-master\dataset\TestImages\test-132.pgm, 52750, 2017-01-03
adaBoost-master\dataset\TestImages\test-133.pgm, 16718, 2017-01-03
adaBoost-master\dataset\TestImages\test-134.pgm, 13294, 2017-01-03
adaBoost-master\dataset\TestImages\test-135.pgm, 22387, 2017-01-03
adaBoost-master\dataset\TestImages\test-136.pgm, 15214, 2017-01-03
adaBoost-master\dataset\TestImages\test-137.pgm, 18195, 2017-01-03
adaBoost-master\dataset\TestImages\test-138.pgm, 13738, 2017-01-03
adaBoost-master\dataset\TestImages\test-139.pgm, 13214, 2017-01-03
adaBoost-master\dataset\TestImages\test-14.pgm, 24315, 2017-01-03
adaBoost-master\dataset\TestImages\test-140.pgm, 23815, 2017-01-03
adaBoost-master\dataset\TestImages\test-141.pgm, 16882, 2017-01-03
adaBoost-master\dataset\TestImages\test-142.pgm, 17834, 2017-01-03
adaBoost-master\dataset\TestImages\test-143.pgm, 27075, 2017-01-03
adaBoost-master\dataset\TestImages\test-144.pgm, 13008, 2017-01-03
adaBoost-master\dataset\TestImages\test-145.pgm, 16075, 2017-01-03
adaBoost-master\dataset\TestImages\test-146.pgm, 19417, 2017-01-03
adaBoost-master\dataset\TestImages\test-147.pgm, 13078, 2017-01-03
adaBoost-master\dataset\TestImages\test-148.pgm, 15211, 2017-01-03
adaBoost-master\dataset\TestImages\test-149.pgm, 14467, 2017-01-03
adaBoost-master\dataset\TestImages\test-15.pgm, 44107, 2017-01-03
adaBoost-master\dataset\TestImages\test-150.pgm, 29499, 2017-01-03
adaBoost-master\dataset\TestImages\test-151.pgm, 12020, 2017-01-03
adaBoost-master\dataset\TestImages\test-152.pgm, 14456, 2017-01-03
adaBoost-master\dataset\TestImages\test-153.pgm, 17752, 2017-01-03
adaBoost-master\dataset\TestImages\test-154.pgm, 17823, 2017-01-03
adaBoost-master\dataset\TestImages\test-155.pgm, 16015, 2017-01-03
adaBoost-master\dataset\TestImages\test-156.pgm, 18915, 2017-01-03
adaBoost-master\dataset\TestImages\test-157.pgm, 15204, 2017-01-03
adaBoost-master\dataset\TestImages\test-158.pgm, 16547, 2017-01-03
adaBoost-master\dataset\TestImages\test-159.pgm, 27485, 2017-01-03
adaBoost-master\dataset\TestImages\test-16.pgm, 24027, 2017-01-03
adaBoost-master\dataset\TestImages\test-160.pgm, 22521, 2017-01-03
adaBoost-master\dataset\TestImages\test-161.pgm, 17823, 2017-01-03
adaBoost-master\dataset\TestImages\test-162.pgm, 17151, 2017-01-03
adaBoost-master\dataset\TestImages\test-163.pgm, 20307, 2017-01-03
adaBoost-master\dataset\TestImages\test-164.pgm, 17915, 2017-01-03
adaBoost-master\dataset\TestImages\test-165.pgm, 37551, 2017-01-03
adaBoost-master\dataset\TestImages\test-166.pgm, 18954, 2017-01-03
adaBoost-master\dataset\TestImages\test-167.pgm, 18936, 2017-01-03
adaBoost-master\dataset\TestImages\test-168.pgm, 18915, 2017-01-03
adaBoost-master\dataset\TestImages\test-169.pgm, 15534, 2017-01-03
adaBoost-master\dataset\TestImages\test-17.pgm, 43755, 2017-01-03
adaBoost-master\dataset\TestImages\test-18.pgm, 63375, 2017-01-03
adaBoost-master\dataset\TestImages\test-19.pgm, 47790, 2017-01-03
adaBoost-master\dataset\TestImages\test-2.pgm, 15764, 2017-01-03
adaBoost-master\dataset\TestImages\test-20.pgm, 16674, 2017-01-03
adaBoost-master\dataset\TestImages\test-21.pgm, 19205, 2017-01-03
adaBoost-master\dataset\TestImages\test-22.pgm, 31505, 2017-01-03
adaBoost-master\dataset\TestImages\test-23.pgm, 22615, 2017-01-03
adaBoost-master\dataset\TestImages\test-24.pgm, 24265, 2017-01-03
adaBoost-master\dataset\TestImages\test-25.pgm, 16845, 2017-01-03
adaBoost-master\dataset\TestImages\test-26.pgm, 38655, 2017-01-03
adaBoost-master\dataset\TestImages\test-27.pgm, 27510, 2017-01-03
adaBoost-master\dataset\TestImages\test-28.pgm, 27037, 2017-01-03
adaBoost-master\dataset\TestImages\test-29.pgm, 22524, 2017-01-03

下载说明：请别用迅雷下载，失败请重下，重下不扣分！

发表评论

0 个回复

  • corrMatching
    correlation matching using matlab it is a code used for match correlation a image in matlab software. using this we can a correlate an image.
    2010-12-26 13:49:30下载
    积分：1
  • HGMEM
    层次性EM算法 VASCONCELOS，(hierarchy EM algorithm VASCONCELOS,)
    2006-12-08 09:35:06下载
    积分：1
  • UWB_matlamatlab
    这是一个全面实现超宽带通信系统的matlab实现的仿真，还不错的(This is a full realization of UWB communications systems to achieve the Matlab simulation, but also good)
    2007-03-29 21:45:07下载
    积分：1
  • BFT
    BFT,正交傅里叶变换，用于检测线性调频斜率的方法。仿真与论文结果一致。(BFT, orthogonal Fourier transform for detecting the slope of the linear frequency modulation method. Simulation results are consistent with the thesis.)
    2013-08-23 13:50:20下载
    积分：1
  • matlab
    关于matlab一些主要功能命令的使用和数学上一些经典算法的matlab的实现(Matlab commands on the use of some of the major features and some classical mathematical algorithm matlab implementation)
    2011-12-27 14:22:54下载
    积分：1
  • send
    open dicom file in matlab
    2012-02-07 14:22:55下载
    积分：1
  • PCA-TEST
    pca算法，有详细注释，通过光谱区分苹果酸甜度，对于想学习pca算法的初学者，有很大帮助(pca algorithm, detailed notes, by spectroscopic distinguish sour apple degree, want to learn pca algorithm for beginners, there are a great help)
    2015-10-12 17:33:32下载
    积分：1
  • cut-off
    用于<数字信号处理及MATLAB实现>的截断效应(For " digital signal processing and MATLAB realization of" cut-off effects of)
    2010-01-13 19:56:31下载
    积分：1
  • libsvm
    说明：  支持向量机（SVM）matlab 代码，附有详细的使用说明及举例讲解。 (This tool provides a simple interface to LIBSVM, a library for support vector machines.)
    2010-04-21 21:30:20下载
    积分：1
  • zhijiejie
    用直接解得办法求摄影测量中的相对定向元素( use direct measurement to find the relative orientation elements in photography)
    2020-12-31 14:58:59下载
    积分：1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载

热门标签

Visual C++ matlab C/C++ Java Others Unix_Linux EasyLanguage易语言 Visual Basic C# PDF C++ Delphi VHDL ASP WINDOWS
热门下载

Copyright© 2019-2026 | Powered by Imdn | 浙ICP备16007336号 | IMDN交流 | 联系客服（QQ：3324461878）

本网站资源收集自网络及网站用户上传，若有侵权请邮件至（3324461878@qq.com），核实后我们会在24小时内删除，谢谢！