Description: 基于hog人体识别的很好的文章，既有基于adaboost的又有svm的分类器。-Hog human identification based on a very good article, both based on the AdaBoost and the SVM classifier. Platform: |
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Author:孙兆辉 |
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Description: 机器学习各种分类器代码，C#。
包括AdaBoost,DecisionStump,NearestNeighbout,SVM等，包括测试数据的生成-A variety of machine learning classifier code, C#. Including AdaBoost, DecisionStump, NearestNeighbout, SVM, including the generation of test data Platform: |
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Author:dyzhao |
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Description: 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(weaker
ifier)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。
-Adaboost algorithm basic idea is: the ability to use the general classification of a large number of weak classifier (weakerifier) through a certain method of superposition (boost), and constitute a strong Category strong classifier eyes eClassifier), then a number of strong Category connected in series to become hierarchical classifier (ClassifierCaseade) image search detection. Adaboost algorithm is to use this article will be generated characteristics category haar weak classifier become strong classifier, and then become a strong tandem Classifier Classifier classification. Platform: |
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Author:wangxuyang |
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Description: AdaBoost, Adaptive Boosting, is a well-known meta machine learning algorithm that was proposed by Yoav Freund and Robert Schapire. In this project there two main files
1. ADABOOST_tr.m
2. ADABOOST_te.m
to traing and test a user-coded learning (classification) algorithm with AdaBoost. A demo file (demo.m) is provided that demonstrates how these two files can be used with a classifier (basic threshold classifier) for two class classification problem.-AdaBoost, Adaptive Boosting, is a well-known meta machine learning algorithm that was proposed by Yoav Freund and Robert Schapire. In this project there two main files 1. ADABOOST_tr.m 2. ADABOOST_te.m to traing and test a user-coded learning (classification) algorithm with AdaBoost. A demo file (demo.m) is provided that demonstrates how these two files can be used with a classifier (basic threshold classifier) for two class classification problem. Platform: |
Size: 6144 |
Author:来海锋 |
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Description: Adaboost实现，主要用于机器学习的多分类器聚合， 最终形成分类效果逐渐增强的分类器-Adaboost implementation, is mainly used for machine learning, multiple classifier aggregation, the final shape classification results show a gradual increase of the classifier Platform: |
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Author:Shannon Liu |
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Description: AdaBoost分类器的源代码的用户手册， 内有原始代码下载网址。-AdaBoost classifier source code of the user manual, there are source code download link. Platform: |
Size: 51200 |
Author:sophie |
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Description: 最经典AdaBoost实现，适合初学，有大量详细的注释，容易理解-This a classic AdaBoost implementation, in one single file with easy understandable code.
The function consist of two parts a simple weak classifier and a boosting part:
The weak classifier tries to find the best threshold in one of the data dimensions to separate the data into two classes-1 and 1
The boosting part calls the classifier iteratively, after every classification step it changes the weights of miss-classified examples. This creates a cascade of "weak classifiers" which behaves like a "strong classifier" 。 Platform: |
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Author:wj |
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Description: Image descriptor based on Histogram of Orientated Gradients for gray-level images. This code
was developed for the work: O. Ludwig, D. Delgado, V. Goncalves, and U. Nunes, Trainable
Classifier-Fusion Schemes: An Application To Pedestrian Detection, In: 12th International IEEE
Conference On Intelligent Transportation Systems, 2009, St. Louis, 2009. V. 1. P. 432-437. In
case of publication with this code, please cite the paper above.- Image descriptor based on Histogram of Orientated Gradients for gray-level images. This code
was developed for the work: O. Ludwig, D. Delgado, V. Goncalves, and U. Nunes, Trainable
Classifier-Fusion Schemes: An Application To Pedestrian Detection, In: 12th International IEEE
Conference On Intelligent Transportation Systems, 2009, St. Louis, 2009. V. 1. P. 432-437. In
case of publication with this code, please cite the paper above. Platform: |
Size: 2048 |
Author:Arij |
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Description: 采用matlab实现了Adaboost分类器算法，有利于学生对分类器的学习！-The function of this code is to implement the Adaboost algorithm using matlab programming language,which is very useful to learn of all kinds of classifier for students, especially for beginners. Platform: |
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Author: |
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Description: adaboost智能算法源程序，将若分类器反复训练得到强分类器，用于二分类问题-adaboost intelligent algorithm source code, will be repeated if the classifier has been trained strong classifier for the two classification Platform: |
Size: 9216 |
Author:豆豆 |
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Description: adaboost 源码，综合多个弱分类器，通过动态修改元组权值以及得到的分类器权值，提升为复合强分类器。-AdaBoost source code, several weak classifiers, by dynamically modifying the tuple classifier obtained by weight and weight, enhance the strong classifier for composite. Platform: |
Size: 9216 |
Author:ss |
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Description: Adaboost的C实现，在原始代码上做了一点小修改，另外加上了详细的注释，能够帮助初学者更好地理解分类器具体如何学习与选择的-Adaboost C implementation, the source code to do a little modification, plus detailed notes, can help beginners to better understand the specifics of how learning and classifier selection Platform: |
Size: 3072 |
Author:yejunjian |
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Description: 经典的Adaboost分类器训练过程详细的matlab代码解释，对做模式识别的人很有用-Classic Adaboost classifier training process explained in detail matlab code, to do pattern recognition is useful Platform: |
Size: 96256 |
Author:伦格 |
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Search - adaboost classifier code