-
Notifications
You must be signed in to change notification settings - Fork 0
/
index.html
12 lines (12 loc) · 24.6 KB
/
index.html
1
2
3
4
5
6
7
8
9
10
11
12
<!-- build time:Sun Jun 03 2018 18:33:06 GMT+0800 (CST) --><!DOCTYPE html><html class="theme-next mist" lang="zh-Hans"><head><meta charset="UTF-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width,initial-scale=1,maximum-scale=1"><meta name="theme-color" content="#222"><meta http-equiv="Cache-Control" content="no-transform"><meta http-equiv="Cache-Control" content="no-siteapp"><link href="/lib/fancybox/source/jquery.fancybox.css?v=2.1.5" rel="stylesheet" type="text/css"><link href="/lib/font-awesome/css/font-awesome.min.css?v=4.6.2" rel="stylesheet" type="text/css"><link href="/css/main.css?v=5.1.3" rel="stylesheet" type="text/css"><link rel="apple-touch-icon" sizes="180x180" href="/images/apple-touch-icon-next.png?v=5.1.3"><link rel="icon" type="image/png" sizes="32x32" href="/images/favicon-32x32-next.png?v=5.1.3"><link rel="icon" type="image/png" sizes="16x16" href="/images/favicon-16x16-next.png?v=5.1.3"><link rel="mask-icon" href="/images/logo.svg?v=5.1.3" color="#222"><meta name="keywords" content="Hexo, NexT"><meta name="description" content="分享机器学习、深度学习的点滴"><meta property="og:type" content="website"><meta property="og:title" content="广阔天地，大有作为"><meta property="og:url" content="laiqun.github.io/index.html"><meta property="og:site_name" content="广阔天地，大有作为"><meta property="og:description" content="分享机器学习、深度学习的点滴"><meta property="og:locale" content="zh-Hans"><meta name="twitter:card" content="summary"><meta name="twitter:title" content="广阔天地，大有作为"><meta name="twitter:description" content="分享机器学习、深度学习的点滴"><script type="text/javascript" id="hexo.configurations">var NexT=window.NexT||{},CONFIG={root:"/",scheme:"Mist",version:"5.1.3",sidebar:{position:"left",display:"post",offset:12,b2t:!1,scrollpercent:!1,onmobile:!0},fancybox:!0,tabs:!0,motion:{enable:!1,async:!1,transition:{post_block:"fadeIn",post_header:"slideDownIn",post_body:"slideDownIn",coll_header:"slideLeftIn",sidebar:"slideUpIn"}},duoshuo:{userId:"0",author:"博主"},algolia:{applicationID:"",apiKey:"",indexName:"",hits:{per_page:10},labels:{input_placeholder:"Search for Posts",hits_empty:"We didn't find any results for the search: ${query}",hits_stats:"${hits} results found in ${time} ms"}}}</script><link rel="canonical" href="laiqun.github.io/"><title>广阔天地，大有作为</title></head><body itemscope itemtype="http://schema.org/WebPage" lang="zh-Hans"><div class="container sidebar-position-left page-home"><div class="headband"></div><header id="header" class="header" itemscope itemtype="http://schema.org/WPHeader"><div class="header-inner"><div class="site-brand-wrapper"><div class="site-meta"><div class="custom-logo-site-title"><a href="/" class="brand" rel="start"><span class="logo-line-before"><i></i></span> <span class="site-title">广阔天地，大有作为</span> <span class="logo-line-after"><i></i></span></a></div><p class="site-subtitle">你看到我的筋斗云了嘛？</p></div><div class="site-nav-toggle"><button><span class="btn-bar"></span> <span class="btn-bar"></span> <span class="btn-bar"></span></button></div></div><nav class="site-nav"><ul id="menu" class="menu"><li class="menu-item menu-item-home"><a href="/" rel="section"><i class="menu-item-icon fa fa-fw fa-home"></i><br>首页</a></li><li class="menu-item menu-item-about"><a href="/about/" rel="section"><i class="menu-item-icon fa fa-fw fa-user"></i><br>关于</a></li><li class="menu-item menu-item-categories"><a href="/categories/" rel="section"><i class="menu-item-icon fa fa-fw fa-th"></i><br>分类</a></li><li class="menu-item menu-item-archives"><a href="/archives/" rel="section"><i class="menu-item-icon fa fa-fw fa-archive"></i><br>归档</a></li></ul></nav></div></header><main id="main" class="main"><div class="main-inner"><div class="content-wrap"><div id="content" class="content"><section id="posts" class="posts-expand"><article class="post post-type-normal" itemscope itemtype="http://schema.org/Article"><div class="post-block"><link itemprop="mainEntityOfPage" href="laiqun.github.io/2018/02/26/advanced-classification/"><span hidden itemprop="author" itemscope itemtype="http://schema.org/Person"><meta itemprop="name" content="倔强的土豆"><meta itemprop="description" content=""><meta itemprop="image" content="/images/avatar.gif"></span><span hidden itemprop="publisher" itemscope itemtype="http://schema.org/Organization"><meta itemprop="name" content="广阔天地，大有作为"></span><header class="post-header"><h1 class="post-title" itemprop="name headline"><a class="post-title-link" href="/2018/02/26/advanced-classification/" itemprop="url">高阶分类：核方法与SVM</a></h1><div class="post-meta"><span class="post-time"><span class="post-meta-item-icon"><i class="fa fa-calendar-o"></i> </span><span class="post-meta-item-text">发表于</span> <time title="创建于" itemprop="dateCreated datePublished" datetime="2018-02-26T22:40:09+08:00">2018-02-26</time></span></div></header><div class="post-body" itemprop="articleBody">前面几章已经讨论了三种分类器：神经网络、决策树、贝叶斯分类器。本章将介绍线性分类器与核方法的概念，并以此为铺垫介绍支持向量机（SVM）。本章要解决的问题是约会网站的用户配对，即给定两人的许多属性，属性有名词型也有数值型，属性直接还存在大量的非线性关系。我们将选用该约会网站的数据集来为大家示范前面几种 ...<div class="post-button text-center"><a class="btn" href="/2018/02/26/advanced-classification/#more" rel="contents">阅读全文 »</a></div></div><footer class="post-footer"><div class="post-eof"></div></footer></div></article><article class="post post-type-normal" itemscope itemtype="http://schema.org/Article"><div class="post-block"><link itemprop="mainEntityOfPage" href="laiqun.github.io/2018/02/23/buildingPriceModels/"><span hidden itemprop="author" itemscope itemtype="http://schema.org/Person"><meta itemprop="name" content="倔强的土豆"><meta itemprop="description" content=""><meta itemprop="image" content="/images/avatar.gif"></span><span hidden itemprop="publisher" itemscope itemtype="http://schema.org/Organization"><meta itemprop="name" content="广阔天地，大有作为"></span><header class="post-header"><h1 class="post-title" itemprop="name headline"><a class="post-title-link" href="/2018/02/23/buildingPriceModels/" itemprop="url">构建价格模型</a></h1><div class="post-meta"><span class="post-time"><span class="post-meta-item-icon"><i class="fa fa-calendar-o"></i> </span><span class="post-meta-item-text">发表于</span> <time title="创建于" itemprop="dateCreated datePublished" datetime="2018-02-23T22:07:14+08:00">2018-02-23</time></span></div></header><div class="post-body" itemprop="articleBody">到目前为止，我们已经考察过了一部分分类器，其中大多数都非常适合对未知数据的所属分类进行预测。但是，在利用多种不同的属性（比如价格、大小）对数值型数据进行预测时，贝叶斯分类器、决策树、以及支持向量机都不是最佳的算法。本章我们将对一系列的算法进行考查：这些算法可以接受训练，根据之前见过的样本数据做出数值 ...<div class="post-button text-center"><a class="btn" href="/2018/02/23/buildingPriceModels/#more" rel="contents">阅读全文 »</a></div></div><footer class="post-footer"><div class="post-eof"></div></footer></div></article><article class="post post-type-normal" itemscope itemtype="http://schema.org/Article"><div class="post-block"><link itemprop="mainEntityOfPage" href="laiqun.github.io/2018/02/02/decision-tree/"><span hidden itemprop="author" itemscope itemtype="http://schema.org/Person"><meta itemprop="name" content="倔强的土豆"><meta itemprop="description" content=""><meta itemprop="image" content="/images/avatar.gif"></span><span hidden itemprop="publisher" itemscope itemtype="http://schema.org/Organization"><meta itemprop="name" content="广阔天地，大有作为"></span><header class="post-header"><h1 class="post-title" itemprop="name headline"><a class="post-title-link" href="/2018/02/02/decision-tree/" itemprop="url">决策树建模</a></h1><div class="post-meta"><span class="post-time"><span class="post-meta-item-icon"><i class="fa fa-calendar-o"></i> </span><span class="post-meta-item-text">发表于</span> <time title="创建于" itemprop="dateCreated datePublished" datetime="2018-02-02T22:50:08+08:00">2018-02-02</time></span></div></header><div class="post-body" itemprop="articleBody">到目前为止，我们已经掌握了几种不同的自动分类器算法，本章我们将对此做进一步的延伸，介绍一种非常有用的算法，叫做决策树学习。不同于其他大多数分类器，由决策树产生的模型具有易于解释的特点——贝叶斯分类器中数字列表会告诉我们每个单词的重要程序，但是你必须经过计算才能得知整篇文档的结果如何。理解神经网络的难 ...<div class="post-button text-center"><a class="btn" href="/2018/02/02/decision-tree/#more" rel="contents">阅读全文 »</a></div></div><footer class="post-footer"><div class="post-eof"></div></footer></div></article><article class="post post-type-normal" itemscope itemtype="http://schema.org/Article"><div class="post-block"><link itemprop="mainEntityOfPage" href="laiqun.github.io/2018/01/22/document-filtering/"><span hidden itemprop="author" itemscope itemtype="http://schema.org/Person"><meta itemprop="name" content="倔强的土豆"><meta itemprop="description" content=""><meta itemprop="image" content="/images/avatar.gif"></span><span hidden itemprop="publisher" itemscope itemtype="http://schema.org/Organization"><meta itemprop="name" content="广阔天地，大有作为"></span><header class="post-header"><h1 class="post-title" itemprop="name headline"><a class="post-title-link" href="/2018/01/22/document-filtering/" itemprop="url">文档过滤</a></h1><div class="post-meta"><span class="post-time"><span class="post-meta-item-icon"><i class="fa fa-calendar-o"></i> </span><span class="post-meta-item-text">发表于</span> <time title="创建于" itemprop="dateCreated datePublished" datetime="2018-01-22T20:26:20+08:00">2018-01-22</time></span></div></header><div class="post-body" itemprop="articleBody">文档过滤本章将向大家演示如何依据内容来对文档进行分类。文档分类是机器智能(machine Intelligence)的一个应用，很有实用价值,而且现在越来越普及。关于文档过滤，最有价值也最为人们所熟知的应用，恐怕要数垃圾邮件过滤了。随着电子邮件的广泛普及与邮件发送的超低成本，人们面临的一大问题是任何 ...<div class="post-button text-center"><a class="btn" href="/2018/01/22/document-filtering/#more" rel="contents">阅读全文 »</a></div></div><footer class="post-footer"><div class="post-eof"></div></footer></div></article><article class="post post-type-normal" itemscope itemtype="http://schema.org/Article"><div class="post-block"><link itemprop="mainEntityOfPage" href="laiqun.github.io/2018/01/07/optimization/"><span hidden itemprop="author" itemscope itemtype="http://schema.org/Person"><meta itemprop="name" content="倔强的土豆"><meta itemprop="description" content=""><meta itemprop="image" content="/images/avatar.gif"></span><span hidden itemprop="publisher" itemscope itemtype="http://schema.org/Organization"><meta itemprop="name" content="广阔天地，大有作为"></span><header class="post-header"><h1 class="post-title" itemprop="name headline"><a class="post-title-link" href="/2018/01/07/optimization/" itemprop="url">优化</a></h1><div class="post-meta"><span class="post-time"><span class="post-meta-item-icon"><i class="fa fa-calendar-o"></i> </span><span class="post-meta-item-text">发表于</span> <time title="创建于" itemprop="dateCreated datePublished" datetime="2018-01-07T16:03:00+08:00">2018-01-07</time></span></div></header><div class="post-body" itemprop="articleBody">优化本章将会教大家，如何使用一系列的随机优化 的技术来解决协作类问题。这种技术擅长处理：结果受多种变量影响有许多可能题解结果是变量的组合，变量组合变化，结果也跟着变应用场景举例：物理学 研究分子的运动生物学 预测蛋白质的结构计算机 确定算法的最坏运行时间NASA 美国国家宇航局使用优化技术来设计具有 ...<div class="post-button text-center"><a class="btn" href="/2018/01/07/optimization/#more" rel="contents">阅读全文 »</a></div></div><footer class="post-footer"><div class="post-eof"></div></footer></div></article><article class="post post-type-normal" itemscope itemtype="http://schema.org/Article"><div class="post-block"><link itemprop="mainEntityOfPage" href="laiqun.github.io/2017/12/02/SearchAndRanking/"><span hidden itemprop="author" itemscope itemtype="http://schema.org/Person"><meta itemprop="name" content="倔强的土豆"><meta itemprop="description" content=""><meta itemprop="image" content="/images/avatar.gif"></span><span hidden itemprop="publisher" itemscope itemtype="http://schema.org/Organization"><meta itemprop="name" content="广阔天地，大有作为"></span><header class="post-header"><h1 class="post-title" itemprop="name headline"><a class="post-title-link" href="/2017/12/02/SearchAndRanking/" itemprop="url">搜索与排名</a></h1><div class="post-meta"><span class="post-time"><span class="post-meta-item-icon"><i class="fa fa-calendar-o"></i> </span><span class="post-meta-item-text">发表于</span> <time title="创建于" itemprop="dateCreated datePublished" datetime="2017-12-02T16:27:03+08:00">2017-12-02</time></span></div></header><div class="post-body" itemprop="articleBody">搜索引擎的定义与组成在大量的文档中搜索一系列单词，根据文档与这些单词的相关程度，对搜索结果进行排名。本章中我们将将学到如何搜索引起的数据处理与数据检索的方法：数据处理：抓取网页（crawl）、建立索引（index）数据检索：从多种角度度量不同文档与搜索关键词的相关程度，根据相关程度对文档进行排序。数 ...<div class="post-button text-center"><a class="btn" href="/2017/12/02/SearchAndRanking/#more" rel="contents">阅读全文 »</a></div></div><footer class="post-footer"><div class="post-eof"></div></footer></div></article><article class="post post-type-normal" itemscope itemtype="http://schema.org/Article"><div class="post-block"><link itemprop="mainEntityOfPage" href="laiqun.github.io/2017/11/12/cluster/"><span hidden itemprop="author" itemscope itemtype="http://schema.org/Person"><meta itemprop="name" content="倔强的土豆"><meta itemprop="description" content=""><meta itemprop="image" content="/images/avatar.gif"></span><span hidden itemprop="publisher" itemscope itemtype="http://schema.org/Organization"><meta itemprop="name" content="广阔天地，大有作为"></span><header class="post-header"><h1 class="post-title" itemprop="name headline"><a class="post-title-link" href="/2017/11/12/cluster/" itemprop="url">发现群组</a></h1><div class="post-meta"><span class="post-time"><span class="post-meta-item-icon"><i class="fa fa-calendar-o"></i> </span><span class="post-meta-item-text">发表于</span> <time title="创建于" itemprop="dateCreated datePublished" datetime="2017-11-12T09:46:33+08:00">2017-11-12</time></span></div></header><div class="post-body" itemprop="articleBody">聚类的概念上一章中讲了如何寻找与自己相似的用户，本章在上一章的思想加以扩展，引入聚类的概念。聚类的概念为：将紧密相关的事物、人或观点聚集在一起，并将其可视化的方法。本章节我们将会学习到以下内容：从不同来源中构造算法所需要的数据两种不同的聚类算法更多的有关距离度量(distance metrics)的 ...<div class="post-button text-center"><a class="btn" href="/2017/11/12/cluster/#more" rel="contents">阅读全文 »</a></div></div><footer class="post-footer"><div class="post-eof"></div></footer></div></article><article class="post post-type-normal" itemscope itemtype="http://schema.org/Article"><div class="post-block"><link itemprop="mainEntityOfPage" href="laiqun.github.io/2017/11/05/Marking-Recommendations/"><span hidden itemprop="author" itemscope itemtype="http://schema.org/Person"><meta itemprop="name" content="倔强的土豆"><meta itemprop="description" content=""><meta itemprop="image" content="/images/avatar.gif"></span><span hidden itemprop="publisher" itemscope itemtype="http://schema.org/Organization"><meta itemprop="name" content="广阔天地，大有作为"></span><header class="post-header"><h1 class="post-title" itemprop="name headline"><a class="post-title-link" href="/2017/11/05/Marking-Recommendations/" itemprop="url">提供推荐</a></h1><div class="post-meta"><span class="post-time"><span class="post-meta-item-icon"><i class="fa fa-calendar-o"></i> </span><span class="post-meta-item-text">发表于</span> <time title="创建于" itemprop="dateCreated datePublished" datetime="2017-11-05T09:42:02+08:00">2017-11-05</time></span></div></header><div class="post-body" itemprop="articleBody">什么是推荐系统？本章要教大家的是：如果构建一个系统，将具有相同品味、爱好的人聚集在一起，根据群体的偏好来为人们提供推荐。这种技术也叫做协作型过滤。其做法是：对一大群人进行搜索找出与我们品味相近的的一小群人对这小群人的偏爱的内容进行考察将这些内容组合起来构成一个经过排名的推荐列表这里的协作，个人理解就 ...<div class="post-button text-center"><a class="btn" href="/2017/11/05/Marking-Recommendations/#more" rel="contents">阅读全文 »</a></div></div><footer class="post-footer"><div class="post-eof"></div></footer></div></article><article class="post post-type-normal" itemscope itemtype="http://schema.org/Article"><div class="post-block"><link itemprop="mainEntityOfPage" href="laiqun.github.io/2017/11/04/introduction-to-collective-intelligence/"><span hidden itemprop="author" itemscope itemtype="http://schema.org/Person"><meta itemprop="name" content="倔强的土豆"><meta itemprop="description" content=""><meta itemprop="image" content="/images/avatar.gif"></span><span hidden itemprop="publisher" itemscope itemtype="http://schema.org/Organization"><meta itemprop="name" content="广阔天地，大有作为"></span><header class="post-header"><h1 class="post-title" itemprop="name headline"><a class="post-title-link" href="/2017/11/04/introduction-to-collective-intelligence/" itemprop="url">集体智慧导言</a></h1><div class="post-meta"><span class="post-time"><span class="post-meta-item-icon"><i class="fa fa-calendar-o"></i> </span><span class="post-meta-item-text">发表于</span> <time title="创建于" itemprop="dateCreated datePublished" datetime="2017-11-04T18:31:56+08:00">2017-11-04</time></span></div></header><div class="post-body" itemprop="articleBody">什么是集体智慧?集体智慧的定义为：为了创造新的想法，而将一群人的行为、偏好、或者思想组合在一起。收集、组合和分析数据,从一大群人中搜集的答案可以使我们得出关于群组的统计结论：组中的个体将被忽视，将成百上千人的想法组合在一起，形成一种不依赖个人观点的结论。寻求集体智慧的例子：wikipediawiki ...<div class="post-button text-center"><a class="btn" href="/2017/11/04/introduction-to-collective-intelligence/#more" rel="contents">阅读全文 »</a></div></div><footer class="post-footer"><div class="post-eof"></div></footer></div></article><article class="post post-type-normal" itemscope itemtype="http://schema.org/Article"><div class="post-block"><link itemprop="mainEntityOfPage" href="laiqun.github.io/2017/11/02/django-commnets-system/"><span hidden itemprop="author" itemscope itemtype="http://schema.org/Person"><meta itemprop="name" content="倔强的土豆"><meta itemprop="description" content=""><meta itemprop="image" content="/images/avatar.gif"></span><span hidden itemprop="publisher" itemscope itemtype="http://schema.org/Organization"><meta itemprop="name" content="广阔天地，大有作为"></span><header class="post-header"><h1 class="post-title" itemprop="name headline"><a class="post-title-link" href="/2017/11/02/django-commnets-system/" itemprop="url">django_commnets_system</a></h1><div class="post-meta"><span class="post-time"><span class="post-meta-item-icon"><i class="fa fa-calendar-o"></i> </span><span class="post-meta-item-text">发表于</span> <time title="创建于" itemprop="dateCreated datePublished" datetime="2017-11-02T22:50:48+08:00">2017-11-02</time></span></div></header><div class="post-body" itemprop="articleBody">测试markdown标记语言xx00xx<div class="post-button text-center"><a class="btn" href="/2017/11/02/django-commnets-system/#more" rel="contents">阅读全文 »</a></div></div><footer class="post-footer"><div class="post-eof"></div></footer></div></article></section></div></div><div class="sidebar-toggle"><div class="sidebar-toggle-line-wrap"><span class="sidebar-toggle-line sidebar-toggle-line-first"></span> <span class="sidebar-toggle-line sidebar-toggle-line-middle"></span> <span class="sidebar-toggle-line sidebar-toggle-line-last"></span></div></div><aside id="sidebar" class="sidebar"><div id="sidebar-dimmer"></div><div class="sidebar-inner"><section class="site-overview-wrap sidebar-panel sidebar-panel-active"><div class="site-overview"><div class="site-author motion-element" itemprop="author" itemscope itemtype="http://schema.org/Person"><p class="site-author-name" itemprop="name">倔强的土豆</p><p class="site-description motion-element" itemprop="description">分享机器学习、深度学习的点滴</p></div><nav class="site-state motion-element"><div class="site-state-item site-state-posts"><a href="/archives/"><span class="site-state-item-count">10</span> <span class="site-state-item-name">日志</span></a></div></nav><div class="links-of-author motion-element"><span class="links-of-author-item"><a href="https://github.com/laiqun" target="_blank" title="GitHub"><i class="fa fa-fw fa-github"></i>GitHub</a> </span><span class="links-of-author-item"><a href="mailto:[email protected]" target="_blank" title="E-Mail"><i class="fa fa-fw fa-envelope"></i>E-Mail</a></span></div></div></section></div></aside></div></main><footer id="footer" class="footer"><div class="footer-inner"><div class="copyright">© <span itemprop="copyrightYear">2018</span> <span class="with-love"><i class="fa fa-user"></i> </span><span class="author" itemprop="copyrightHolder">倔强的土豆</span></div><div class="powered-by">由 <a class="theme-link" target="_blank" href="https://hexo.io">Hexo</a> 强力驱动</div><span class="post-meta-divider">|</span><div class="theme-info">主题 — <a class="theme-link" target="_blank" href="https://github.com/iissnan/hexo-theme-next">NexT.Mist</a> v5.1.3</div></div></footer><div class="back-to-top"><i class="fa fa-arrow-up"></i></div></div><script type="text/javascript">"[object Function]"!==Object.prototype.toString.call(window.Promise)&&(window.Promise=null)</script><script type="text/javascript" src="/lib/jquery/index.js?v=2.1.3"></script><script type="text/javascript" src="/lib/fastclick/lib/fastclick.min.js?v=1.0.6"></script><script type="text/javascript" src="/lib/jquery_lazyload/jquery.lazyload.js?v=1.9.7"></script><script type="text/javascript" src="/lib/velocity/velocity.min.js?v=1.2.1"></script><script type="text/javascript" src="/lib/velocity/velocity.ui.min.js?v=1.2.1"></script><script type="text/javascript" src="/lib/fancybox/source/jquery.fancybox.pack.js?v=2.1.5"></script><script type="text/javascript" src="/js/src/utils.js?v=5.1.3"></script><script type="text/javascript" src="/js/src/motion.js?v=5.1.3"></script><script type="text/javascript" src="/js/src/bootstrap.js?v=5.1.3"></script><link rel="stylesheet" href="https://aimingoo.github.io/gitmint/style/default.css"><script src="https://aimingoo.github.io/gitmint/dist/gitmint.browser.js"></script><script type="text/x-mathjax-config">MathJax.Hub.Config({
tex2jax: {
inlineMath: [ ['$','$'], ["\\(","\\)"] ],
processEscapes: true,
skipTags: ['script', 'noscript', 'style', 'textarea', 'pre', 'code']
}
});</script><script type="text/x-mathjax-config">MathJax.Hub.Queue(function() {
var all = MathJax.Hub.getAllJax(), i;
for (i=0; i < all.length; i += 1) {
all[i].SourceElement().parentNode.className += ' has-jax';
}
});</script><script type="text/javascript" src="//cdn.bootcss.com/mathjax/2.7.1/latest.js?config=TeX-AMS-MML_HTMLorMML"></script></body></html><!-- rebuild by neat -->