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人脸检测。用c++编写。人脸检测是人脸分析的首要环节，其处理的问题是确认图像（或影像）中是
否存在人脸，如果存在则对人脸进行定位。人脸检测的应用领域相当广泛，是实
现机器智能化的重要步骤之一。
AdaBoost 算法是1995 年提出的一种快速人脸检测算法，是人脸检测领域里
程碑式的进步，这种算法根据弱学习的反馈，适应性地调整假设的错误率，使在
效率不降低的情况下，检测正确率得到了很大的提高。-Face Detection. Using c++ to prepare. Fac
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集成 学 习 算法通过训练多个弱学习算法并将其结论进行合成，可以显著地提
高学习系统的泛化能力。Boosting算法作为集成学习算法的主要代表算法，得到
了广泛的研究和应用，但其研究成果大部分都集中的分类问题上。-Integrated learning algorithm through the training of more than a weak learning algorithm and its conclusions synthesis, can significantly
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它试图解决的问题，薄弱的标签是一个多学习一种新标签的问题，其中只有部分标签集与每个提供相关培训的例子-This package includes the MATLAB code of the multi-label learning algorithm WELL. It tries to deal with weak label problem which is a new kind of multi-label learning problem, where only a partial la
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adaboost 测试，te_func_handle is a handle to the testing function of a
learning (weak) algorithm whose prototype is shown below.-te_func_handle is a handle to the testing function of a
learning (weak) algorithm whose prototype is shown
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One challenging problem for search-based face annotation scheme is how to effectively perform annotation by exploiting the list of most similar facial images and their weak labels that are often noisy and incomplete. To tackle this problem, we propos
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The package includes the MATLAB code of the multi-instance multi-label learning algorithm MIMLwel, which solves the multi-instance multi-label problem under weak label assumption -The package includes the MATLAB code of the multi-instance multi-label
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简单五子棋，简单学习算法，很弱的AI，原文是Python语句，现改写位c++(Simple backgammon, simple learning algorithm, very weak AI, the original is a Python statement, is now rewritten bit c++)
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boosting算法用于集成学习，包含多种弱分类器(Boosting algorithm is used for ensemble learning, and it contains many weak classifiers)
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