Boosting is a meta-learning approach that aims at combining an ensemble of weak classifiers to form
Boosting is a meta-learning approach that aims at combining an ensemble of weak classifiers to form a strong classifier....
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Boosting is a meta-learning approach that aims at combining an ensemble of weak classifiers to form a strong classifier....
主要是KNN(the k-nearest neighbor algorithm ),LVQ1(learning vector quantization 1), DSM(decision surface mapping)算法。 and a ...
图像配准理论及算法研究.pdf cnn_tutorial.pdf Deep Learning(深度学习)学习笔记整理.pdf 00.神经⽹络与深度学习.pdf deep learning.pdf 深度学习方法及应用PDF高清晰完整版.pdf...
web 2.0 application,uses the ajax technology,is a good usecase for ajax learning ,contain the whole aspects of ajax,view...
决策树,Machine Learning, Tom Mitchell, McGraw Hill,第3章决策树源码
The adaptive hough transform(21HT) 作者:J.Kittler,自适应霍夫变换方法的作者,IEEE的原文,从图书馆找的。
·期刊论文:An Adaptive Frame Skipping and VOP Interpolation Algorithm for Video Object Segmentation