搜索资源列表
mppdf
- 多分类器集成算法，应用前景广泛，本pdf有益于对该算法的了解和学习，共享之。-multiple classifiers integration algorithm, broad application prospects, the benefits of this algorithm pdf understanding and learning, Sharing.
MLC21NT-C
- machine learning, accuracy estimation, cross-validation, bootstrap, ID3, decision trees, decision graphs, naive-bayes, decision tables, majority, induction algorithms, classifiers, categorizers, general logic diagrams, instance-based algorit
classifier
- 一个很好的文本分类器，采用朴素贝叶斯分类的方法，并加以改进！-a very good text classifiers using Bayesian classification methods, and improved!
Boosted_Bayesian_Network_Classifier
- 基于文献《Boosted Bayesian Network Classifiers》的实现代码。
onlineboost
- On-line AdaBoost分类器，AdaBoost分类器的改进，在线学习更新分类器，多用于目标跟踪-On-line AdaBoost classifier, AdaBoost classifiers to improve online learning update classifier, used for target tracking
Eyw4UsersTutorial01
- eyedetection code which first detects a face ,then creates an roi near the eye region and detects an eye.This uses the Haar classifiers in OPEN CV
Ada_Boost
- adaboost源码Adaboost是一种迭代算法，其核心思想是针对同一个训练集训练不同的分类器(弱分类器)，然后把这些弱分类器集合起来，构成一个更强的最终分类器(强分类器)。-adaboost source is an iterative algorithm Adaboost, the core idea is that a training set for the same training the different classifiers (weak classifier), then
ROC
- VB编写的ROC程序，用于对不同的分类器进行评价-VB, ROC procedures used to evaluate the different classifiers
objectdet20070707
- cvpr07年 对象检测代码 hog+svm，压缩包里含有行人，车辆等分类器，可以直接检测-cvpr07 on object identification code hog+ svm, compression bag with pedestrians, vehicles and other classifiers
paper1
- Paper error correlations and error reduction in ensemble classifiers
Adaboost(CPP)
- AdaBoost 是一种将弱分类器线性结合成强分类器的方法，由Jiri Matas 和 Jan Sˇ ochman提出-AdaBoost is a linear combination of the weak classifiers into a strong classifier method, by Jiri Matas and Jan S ochman proposed
VC-dimension
- VC-dimension for characterizing classifiers
supp
- Providing a unique perspective on the state of the art in SVMs, with a particular focus on classification, this thoroughly updated new edition includes a more rigorous performance comparison of classifiers and regressors. In addition to presenting va
Software-faults-prediction-using-multiple-classif
- Abstract—In recent years, the use of machine learning algorithms (classifiers) has proven to be of great value in solving a variety of problems in software engineering including software faults prediction. This paper extends the idea of predi
OHaarTrainingP
- OPENCV训练过程的说明文档，在样本创建；训练分类器；利用训练器进行目标检测测作了操作说明源程序在安装OPENCV时，自带apps\HaarTraining -Documentation of the OPENCV training process, created in the sample train classifiers trainer for target detection measurements have been operating instructions when
AsimpleABdemod
- Adaboost算法的基本思想是:利用大量的分类能力一般的弱分类器(weakerifier)通过一定的方法叠加(boost)起来，构成一个分类能力很强的强分类器眼eClassifier)，再将将若干个强分类器串联成为分级分类器(ClassifierCaseade)图像搜索检测。本文就是利用Adaboost算法将由类haar特征生成的弱分类器成为强分类器，再将强分类器串联成为分级分类器。 -The basic idea of Adaboost algorithm i
Face-Recognition
- 这是一个实现人脸检测的程序，里面有几种人脸检测的分类器。-This is a face detection program, there are several classifiers for face detection.
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
Bayesian-Classify
- 基于贝叶斯网络的分类器实现，使用C++编写，不错，可以参考-Based on Bayesian network classifiers achieve C++ writing, yes, you can reference
Neural-network-classifiers-in-matlab
- The following Matlab project contains the source code and Matlab examples used for neural network classifiers. Fast implementation of the GRLVQ, SRNG and H2MGLVQ algorithms, three supervised LVQ classifiers Please run mexme_NN to recompile mex files