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 ...
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决策树,Machine Learning, Tom Mitchell, McGraw Hill,第3章决策树源码
算法实现:Jieping Ye. Generalized low rank approximations of matrices. Machine Learning, Vol. 61, pp. 167-191, 2005.
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