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dhtmlxTree
- 利用DHTML、Javascr ipt和CSS完成的功能比较全面的树桩控件，操作方便，界面友好-The use of DHTML, Javascr ipt and CSS to complete the function of a more comprehensive tree stump control, easy to operate, user-friendly
wekacode
- java实现CODE weka里面算法的功能，对我们前期学习有所帮助 -weka code
EMP-shape
- 这是国外关于addaboot算法中，gentle boost算法采用stump分类器所得出结果比direct boost 和real boost 算法好的实验论文。-This is abroad on addaboot algorithm, gentle boost classifier algorithm stump than direct boost the outcome of the algorithm and the real
gentleboost
- 温柔的形变模型分类器和两个不同的weak-learners决定树桩和感知。 问题是进行多层次的one-vs-all策略-Gentle AdaBoost Classifier with two different weak-learners : Decision Stump and Perceptron. Multi-class problem is performed with the one-vs-all strateg
AdaboostCode
- 用python实现的adaboost算法，其中基分类器为树桩分类器，并附有训练数据-Adaboost algorithm implemented with python, which base classifiers for stump classifier, along with training data
AdaBoost-Stump
- Adaboost的C++实现，编译成DLL工程，可直接调用，欢迎交流-Adaboost C++ implementation, compiled into a DLL project, can be called directly, welcomed the exchange of
adaboost
- Now, you ought to implement the AdaBoost.M1 and AdaBoost.M2 algorithms. These algorithms are two versions of the AdaBoost algorithm for handling the Problems with more than two classes. You must first read the paper
centaurus
- 一款非常不错的前端框架，包括绚丽的表格、多种图表（树桩统计图、饼状统计图、曲线统计图等待）、邮件发送功能、图片上传以及日期、文本编辑器等等组件- 一款非常不错的前端框架，包括绚丽的表格、多种图表（树桩统计图、饼状统计图、曲线统计图等待）、邮件发送功能、图片上传以及日期、文本编辑器等等组件 A very good and the front end of the fr a me, include the magnificen
19107matlab自编svm
- 利用原算法adaboost弱学习器基于决策树桩的方法对样本数据进行多分类(Multi-classification of sample data based on decision tree stump using AdaBoost weak learner)