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在大数据时代，数据挖掘是最关键的工作。大数据的挖掘是从海量、不完全的、有噪声的、模糊的、随机的大型数据库中发现隐含在其中有价值的、潜在有用的信息和知识的过程，也是一种决策支持过程。其主要基于人工智能，机器学习，模式学习，统计学等。通过对大数据高度自动化地分析，做出归纳性的推理，从中挖掘出潜在的模式，
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在有监督的机器学习中，经常会说到训练集（train)、验证集（validation）和测试集（test），这三个集合的区分可能会让人糊涂，特别是，有些读者搞不清楚验证集和测试集有什么区别。
I. 划分
如果我们自己已经有了一个大的标注数据集，想要完成一个有监督模型的测试，那么通常使用均匀随机抽样的方
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写论文的时候经常使用Visio来画图，然而用Latex排版论文的话，只能插入.eps格式的图片文件。怎么才能方便的插入图片呢？参考下面的文章：
http://blog.csdn.net/kbawyg/article/details/8926113
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<a class="post-title-link" href="/2017/07/23/为什么选择Python而不是Matlab/" itemprop="url">为什么选择Python而不是Matlab</a></h1>
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随着Python语言越来越火，功能越来越强大，使用的人越来越多，在实验室或者应用上都用的越来越多。我觉得是时候全力用上Python了。
放弃MATLAB！简述winpython为什么比MATLAB更方便：
http://www.cnblogs.com/starimpact/p/3526146.htm
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