...2.2.1 术语定义 实例(instance)(x) 属性(attribute) 目标概念(target concept) : c(x) 训练样例(training examples) () 正例(positive example) 、反例 (negative example): c(x)=1 or 0 所有可能假设(all possible hypotheses) : H(c的所有...
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Naive Bayes classifiers often break down when the size of the training examples per class are not balanced or when the data is not independent enough.
当各类的训练示例的大小不平衡,或者数据的独立性不符合要求时,Naive Bayes分类器会出现故障。
This method greatly reduces the number of training examples and so improves the training speed of SVM, without the loss in generalization performance.
在保证支撑矢量机的分类能力情况下,该方法大大地减少了训练样本的个数,同时提高了支撑矢量机的训练速度。
The key problem of training support vector machines is how to solve quadratic programming problem, but for large training examples, the problem is too difficult.
训练支持向量机的本质问题就是求解二次规划问题,但对大规模的训练样本来说,求解二次规划问题困难很大。
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