搜索资源列表
Ada_Boost
- Adaboost集成学习算法 matlab代码-Adaboost
call-Video-achieve-face-detection
- 调用视频实现人脸识别。基于haarcascades+adaboost算法使用opencv实现-Call the video face recognition. Use opencv achieve haarcascades+adaboost algorithm
myfacedet02
- matlab代码程序，利用Adaboost算法训练人脸图像和非人脸图像，通过迭代得到由多个弱分类器组合而成的强分类器，实现图片里的人脸检测。-Matlab code，Using Adaboost algorithm to train the face images and not face images, obtained strong classifier which is conprised of multiple weak classifiers by iteration ， re
Adaboost-(1)
- Adaboost算法的matlab代码，用于演示很不错-Adaboost algorithm matlab code for presentation was very good
adaboost
- 数据挖掘 adaboost算法 java 实现分类问题回归问题 处理离散变量。连续变量-Data mining java adaboost algorithms Deal with regression, classification Handling discrete variables, continuous variables
AdaboostCode
- 用python实现的adaboost算法，其中基分类器为树桩分类器，并附有训练数据-Adaboost algorithm implemented with python, which base classifiers for stump classifier, along with training data
1
- 数据分类，AdaBoost算法提升SVM，MATLAB算法-it is useful。
Adaboost-MATLAB
- 人脸检测,采用Matlab实现的，一种典型的机器学习算法-face decting
Adaboost-
- 在VS环境中,对adaboost算法的实现-In VS environment，adaboost algorithm implementation
adaboost
- 一个关于adaboost算法的matlab程序，这是我开始接触adaboost研究的程序，有实用价值-this is a adaboost algorithm write with matlab code,and it is my starting program of researching work on adaboost,it is valuable for application
AdaBoost
- 用Python实现了Adaboost算法(The Adaboost algorithm is implemented with Python)
拟合代码
- 仿真处理光纤数据，一种简单的拟合方法，易学。附赠adaboost算法论文一篇(photonic crystal fiber dispersion fitting curve based on matlab)
AdaBoost算法实现
- AdaBoost算法实现，你可以使用这个程序运行进行数据分类(AdaBoost algorithm, you can use this program to run data classification)
89123030face_recognition_adaBoost_M2
- 有级联分类器和haar特征和积分图，内部有matlab程序，适合初学者使用(There are cascading classifiers and Haar features and integral graphs, with MATLAB programs inside, suitable for beginners to use)
Adaboost
- 用MATLAB实现Adaboost分类算法，只是一个简单的功能(Using MATLAB to implement Adaboost classification algorithm, it is just a simple function)
19107matlab自编svm
- 利用原算法adaboost弱学习器基于决策树桩的方法对样本数据进行多分类(Multi-classification of sample data based on decision tree stump using AdaBoost weak learner)