【单峰子集分离的迭代算法】 概念：

While labeled data is expensive to prepare, ever increasing amounts of unlabeled data is becoming widely available. In order to adapt to this phenomenon, several semi-supervised learning (SSL) algorithms, which learn from labeled as well as unlabeled data, have been developed. In a separate line of work, researchers have started to realize that graphs provide a natural way to represent data in a variety of domains. Graph-based SSL algorithms, which bring together these two lines of work, have been shown to outperform the state-of-the-art in many applications in speech processing, computer vision, natural language processing, and other areas of Artificial Intelligence. Recognizing this promising and emerging area of research, this synthesis lecture focuses on graphbased SSL algorithms (e.g., label propagation methods). Our hope is that after reading this book, the reader will walk away with the following: (1) an in-depth knowledge of the current stateof- the-art in graph-based SSL algorithms, and the ability to implement them; (2) the ability to decide on the suitability of graph-based SSL methods for a problem; and (3) familiarity with different applications where graph-based SSL methods have been successfully applied.

JSP四大域对象和JSTL、EL表达式

java约苗秒杀，老版本仅供参考使用.zip

文本分割作为监督学习任务 该存储库包含代码和补充材料，这些信息和补充材料是训练和评估模型所必需的，如论文“将 Downalod所需资源 wiki-727K，wiki-50数据集： word2vec： 在configgenerator.py中填充相关路径，并执行脚本（git存储库包括Choi数据集） 创建环境： conda create -n textseg python=2.7 numpy scipy gensim ipython source activate textseg pip install http://download.pytorch.org/whl/cu80/torch

机器学习通过对数据进行预测来分析研究和构造算法，根据输入建立模型，以做出决策或预测。我们研究了不同的机器学习方法及其技术，作了一个简单的分类及总结，适合机器学习的初始学习者阅读。

day_03_运算符、流程控制、循环

java搭建 eclipse的class使用

day_04_循环、方法、总结练习题讲解

该数据集前8行用于描述数据信息，后面的每一行为一个样本，一行有4列，前三列为特征，最后一列为对应数据标签。该数据集可用于监督学习。