There are many ways for constructing classifier 有许多模型用来构造分类器。
Classification is an important sub - branch of data mining , which aims to build the classifier used to predict the class label of new coming data 分类( classification )是数据挖掘领域的一个重要研究分支,分类首先要构造分类器,并对依据分类器对新数据进行类别预测。
Mining classification rules is a procedure to construct a classifier through studying the training dataset . it is a very important part of data mining and knowledge discovery 分类规则挖掘则是通过对训练样本数据集的学习构造分类规则的过程,是数据挖掘、知识发现的一个重要方面。
That is to say , how to make algorithm effective in large dataset is same to small dataset . this measure main idea is reduce primary occupation in order to improve the efficiency of algorithm 即如何使得算法对海量的数据集同小量的数据集一样具有很高的效率,减少内存的限制,提高构造分类器的效率。
In the final , the thesis build a rapid face detection system using a cascaded classifiers based on adaboost learning algorithm , harr - like feature and the method of building classifier 最后本文运用基于adaboost学习算法和harr - like特征及本文提出的由特征构造分类器方法,采用一种分级分类器的结构,搭建了一个快速的人脸检测系统。